The Index Research & Design team is responsible for the research, development and design of indices and index-related analytics across asset classes.

The successful candidate will combine strong quantitative investment expertise with practical index research and development experience.

Key Responsibilities

• Index Research and Innovation
• Lead and contribute to the research, design and quantitative testing of new index methodologies and investment solutions.
• Develop and refine investment metrics, portfolio construction frameworks and analytical methodologies used in index design and evaluation.
• Conduct in-depth quantitative investment research across Asia Pacific markets.
• Analyze the potential portfolio impact of new investment concepts, data sets and index methodologies.
• Develop research papers, analytical materials and presentations.
• Identify emerging market and investment trends.

• Quantitative Analytics and Research Tools
• Develop investment analytics, research applications and tools.
• Build efficient and scalable analytical solutions using Python.
• Apply quantitative techniques including portfolio simulation, optimization and factor analysis.
• Work closely with Technology and other research teams.

• Index Development and Governance
• Support the development and implementation of index methodologies.
• Conduct detailed analysis to ensure proposed methodologies are robust and transparent.
• Provide analytical support for index methodology decisions.
• Work closely with Index Policy, Product Management and other stakeholders.

• Client and Stakeholder Engagement
• Work closely with Product Management, Sales and other client-facing teams.
• Participate in client meetings and present quantitative research and index methodologies.
• Develop trusted working relationships with internal and external stakeholders.
• Support the creation of client presentations and research materials.

• Team Contribution and Development
• Take ownership of assigned research projects and deliver high-quality work.
• Provide technical guidance and support to junior researchers.
• Promote knowledge sharing and collaboration across the team.

Qualifications and Experience

• 5+ years of relevant experience in quantitative investment research, index research or a related field.
• Strong knowledge of quantitative investment techniques and index construction.
• Experience conducting quantitative investment research and translating research concepts into practical investment or index solutions.
• Strong programming and analytical capabilities, with substantial experience using Python and SQL.
• Experience using common Python analytical libraries and data visualization tools.
• Familiarity with large financial datasets and scalable research workflows.
• Understanding of global financial markets and investment products.
• Strong written and verbal communication skills.
• Ability to work effectively across functions and geographies.

Key Behaviours

• Integrity
• Partnership
• Innovation
• Excellence
• Client Focus

Job Data by YubHub.

The Index Research & Design team is responsible for the research, development and design of indices and index-related analytics across asset classes.

The successful candidate will combine strong quantitative investment expertise with practical index research and development experience.

Key Responsibilities

• Index Research and Innovation

Lead and contribute to the research, design and quantitative testing of new index methodologies and investment solutions. Develop and refine investment metrics, portfolio construction frameworks and analytical methodologies used in index design and evaluation. Conduct in-depth quantitative investment research across Asia Pacific markets. Analyze the potential portfolio impact of new investment concepts, data sets and index methodologies. Develop research papers, analytical materials and presentations. Identify emerging market and investment trends.

• Quantitative Analytics and Research Tools

Develop investment analytics, research applications and tools. Build efficient and scalable analytical solutions using Python. Apply quantitative techniques including portfolio simulation, optimization and factor analysis. Work closely with Technology and other research teams. Contribute to the ongoing enhancement of research processes.

• Index Development and Governance

Support the development and implementation of index methodologies. Conduct detailed analysis to ensure proposed methodologies are robust and transparent. Provide analytical support for index methodology decisions. Work closely with Index Policy, Product Management and other stakeholders. Maintain high standards of analytical accuracy and documentation.

• Client and Stakeholder Engagement

Work closely with Product Management, Sales and other client-facing teams. Participate in client meetings and present quantitative research and index methodologies. Develop trusted working relationships with internal and external stakeholders. Support the creation of client presentations and research materials. Collaborate effectively with regional and global research colleagues.

• Team Contribution and Development

Take ownership of assigned research projects and deliver high-quality work. Provide technical guidance and support to junior researchers. Promote knowledge sharing and collaboration across the team. Contribute actively to the team's research agenda and strategic priorities.

Qualifications and Experience The successful candidate should have:

• 5+ years of relevant experience in quantitative investment research, index research or a related field.
• Strong knowledge of quantitative investment techniques and index construction.
• Experience conducting quantitative investment research and translating research concepts into practical investment or index solutions.
• Strong programming and analytical capabilities, with substantial experience using Python and SQL.
• Experience using common Python analytical libraries and data visualization tools.
• Familiarity with large financial datasets and scalable research workflows.
• Understanding of global financial markets and investment products.
• Experience with factor, thematic and/or sustainability-related investment research would be advantageous.
• Strong written and verbal communication skills.
• Ability to work effectively across functions and geographies.
• Bachelor's degree or above in finance, economics, mathematics, statistics, engineering, computer science or another relevant quantitative discipline.
• Fluency in English.

Key Behaviours

• Integrity
• Partnership
• Innovation
• Excellence
• Client Focus

Job Data by YubHub.

You will:

• Design, write, review, and ship production software, primarily in Python
• Own technical direction and architecture for a defined area of the platform
• Lead the design of software systems with resilience, performance, maintainability, and reusability designed in
• Drive engineering quality across the team
• Mentor and coach engineers
• Dig into technical design and risk trade-offs
• Design data-intensive software across relational databases and AWS services
• Build software that processes data at scale on AWS
• Embed observability, automated testing, monitoring, and quality controls
• Take ownership of production outcomes
• Influence and collaborate across engineering teams

You will bring:

• Depth in software design and architecture
• Strong ownership of technical and production outcomes
• Experience with relational databases and AWS
• Excellent communication skills
• A collaborative approach to engineering

Nice to haves:

• Apache Spark / PySpark
• Big data experience
• Apache Iceberg, Delta Lake, or similar open table formats
• CI/CD tooling
• Infrastructure as code
• Experience in financial markets, index data, or investment analytics

Job Data by YubHub.

Responsibilities:

• Writing clean, maintainable production code, primarily in Python, with guidance and support from more experienced engineers
• Building and enhancing software components, services, APIs, and shared libraries as part of a collaborative engineering team
• Writing automated tests and learning how to build software that is reliable, secure, and easy to maintain
• Participating in code reviews , learning from feedback on your own code and gradually developing the skills to review the work of others
• Investigating bugs and production issues, understanding root causes, and implementing well-tested fixes
• Working with relational databases such as Aurora PostgreSQL, learning good practices around data modelling, queries, and schema evolution
• Developing software running on AWS using technologies such as Lambda, containerised services, object storage, and other managed AWS services
• Contributing to data-intensive applications that process significant volumes of financial and index data
• Using CI/CD pipelines and development tooling to build, test, and deploy software safely
• Learning how observability, logging, monitoring, and quality controls help us operate reliable production systems
• Working closely with engineers, product colleagues, and other stakeholders to understand requirements and deliver useful solutions
• Taking part in design discussions and learning how experienced engineers evaluate technical options and trade-offs
• Building knowledge of financial indices and understanding how the software you develop supports our customers
• Continuously developing your engineering skills through hands-on work, feedback, pairing, and knowledge sharing

Requirements:

• A foundation in software development gained through professional experience, internships, graduate programmes, university projects, open-source contributions, or substantial personal projects
• Programming experience in Python or another modern language such as Java, C#, C, C++, Scala, Go, or Rust, together with a willingness to develop strong Python skills
• Understanding of core software engineering concepts such as functions, classes, data structures, APIs, error handling, and automated testing
• An interest in writing readable, maintainable code rather than simply making something work
• Basic understanding of software development practices such as version control, code review, testing, and debugging
• Familiarity with Git or another source control system
• Basic knowledge of relational databases and SQL
• An analytical approach to problem solving and the ability to break problems into smaller, manageable pieces
• Curiosity and willingness to learn new technologies, tools, and engineering practices
• Openness to feedback and an interest in learning from more experienced engineers
• Good communication skills and the confidence to ask questions when something is unclear
• A collaborative mindset , you enjoy solving problems with others and contributing to a supportive engineering environment

Nice to Haves:

• Experience building applications, APIs, services, or libraries in Python
• Familiarity with Python development practices such as type hints, pytest, linters, and dependency management
• Exposure to AWS or another public cloud platform
• Experience with PostgreSQL or another relational database
• Understanding of REST APIs and distributed or service-based architectures
• Experience with Docker or containerised applications
• Familiarity with CI/CD tooling such as GitLab CI, Jenkins, or GitHub Actions
• Exposure to infrastructure as code such as Terraform or AWS CDK
• Experience with data processing, ETL, or data-intensive applications
• Exposure to Pandas, Apache Spark / PySpark, or similar data-processing technologies
• Familiarity with object storage, data lakes, or technologies such as Apache Iceberg
• Contributions to open-source projects or personal software projects you can talk us through
• Experience in financial markets, financial data, or investment analytics
• An interest in financial markets and a willingness to learn the index domain

Job Data by YubHub.

You will lead a team of quantitative researchers in China and serve as a senior representative of Index Research & Design with clients, partners and internal participants.

The successful candidate will combine deep investment and index expertise with strong commercial awareness, leadership capability and an extensive understanding of the China financial market ecosystem.

Key Responsibilities

• Lead and develop a team of index research professionals in China, establishing clear priorities, developing talent and building a high-performing and collaborative research team.
• Provide strategic leadership for FTSE Russell's China research agenda and help shape the broader China index strategy and product roadmap.
• Develop a deep understanding of local market dynamics, regulatory developments, investor trends and driven developments, translating these insights into actionable index opportunities.
• Partner closely with Sales and Product Management to identify strategic growth opportunities and develop index solutions that address evolving client and market needs.
• Represent FTSE Russell externally as a senior subject matter expert and inspiring leader at client meetings, industry conferences, seminars and other market forums.

Index Research and Innovation

• Define and lead research initiatives and index development priorities tailored to the China market.
• Apply quantitative investment techniques, portfolio construction methodologies and market insights to develop commercially relevant index solutions.
• Conduct and oversee investment research and the production of high-quality research papers, presentations and client materials.
• Identify emerging investment themes, product trends and areas of index innovation that can contribute to organic growth.

Client and Stakeholder Engagement

• Act as a trusted senior adviser and subject matter expert to major ETF issuers, asset managers, asset owners, and institutional clients.
• Engage directly with clients to understand investment objectives and translate them into appropriate index and analytical solutions.
• Partner across Product Management, Sales, Index Policy, Technology, Operations and other global Research teams to bring research concepts through to scalable, production-ready indices.
• Connect China opportunities with FTSE Russell's global research and product capabilities, facilitating collaboration and knowledge sharing across regions.

Qualifications and Experience

• 10+ years of confirmed experience within an index provider, asset manager, securities firm, investment bank, asset owner or other relevant financial institution.
• Proven experience leading, developing and motivating research or investment professionals.
• Deep knowledge of the China investment landscape, including the asset-management, ETF and institutional-investor ecosystem and the regulatory and driven dynamics affecting index adoption.
• Extensive knowledge of quantitative investment, including equity style and factor models, portfolio construction, index methodology and quantitative analysis.
• Strong quantitative and analytical capabilities and familiarity with modern data and research environments. Experience with Python, SQL, cloud platforms and related analytical tools is highly desirable.
• Strong communication, presentation and influencing skills, with demonstrated ability to present investment research and strategic recommendations to senior clients and at industry events.
• Fluency in Mandarin Chinese and English, with the ability to operate effectively with both local China partners and global teams.

Job Data by YubHub.

The Business Analyst will identify and shape opportunities for new products, product enhancements, platform transformation, automation, data improvements and operating model change.

Key Responsibilities:

• Elicit, analyse and document business, functional and non-functional requirements, focusing on stakeholder needs, intended outcomes and measurable value.
• Support the delivery of new and enhanced FTSE Russell FICC indices, benchmarks, data services and related capabilities from initial concept through implementation and transition to business-as-usual.
• Produce clear business requirements, process maps, user stories, acceptance criteria, impact assessments and other analysis artefacts appropriate to the delivery methodology.
• Work across Product, Engineering and Operations to assess solution options, dependencies, risks, controls, operational readiness and implementation impacts.
• Translate index methodologies, benchmark requirements, data specifications and business rules into clear requirements that can be implemented and tested.
• Plan and coordinate business testing and user acceptance testing, including test scenarios, expected results, traceability, defect management and business sign-off.
• Identify opportunities to improve processes through automation, standardisation, simplification and better use of data and technology.
• Support platform migrations, system modernisation, data onboarding, vendor or third-party integration and decommissioning activity across the FICC estate.
• Assess data sourcing, quality, lineage, licensing and operational considerations, working with internal teams and external providers where required.
• Contribute to governance, change control, risk assessment, operational resilience and control design, ensuring solutions are sustainable and appropriately documented.
• Facilitate workshops, working groups and decision-making forums, presenting complex information clearly and constructively challenging assumptions where needed.
• Build effective relationships with stakeholders across regions and functions, ensuring timely communication of scope, decisions, changes, issues and dependencies.
• Support responses to regulatory, policy, audit or methodology changes relevant to FTSE Russell indices and benchmarks.

Required Skills:

• Significant business analysis, change delivery or product implementation experience gained within financial services, market data, index/benchmark administration, banking, broking, asset management or a data/vendor environment.
• Good understanding of financial markets and one or more FICC or index-related areas, such as fixed income, interest rates, foreign exchange, commodities, digital assets, index methodologies or benchmark administration.
• Strong requirements elicitation and analysis skills, with the confidence to challenge scope, assumptions, outcomes and proposed solutions.
• Experience producing high-quality requirements, process models, user stories, acceptance criteria, impact assessments and test documentation.
• Strong stakeholder management and facilitation skills, with the ability to communicate effectively across Product, Engineering, Operations, Risk and other business functions.
• Experience of working within a regulated and controlled environment, with an understanding of governance, risk, controls, data quality and operational resilience.
• Good understanding of software and product development lifecycles, including agile and iterative delivery approaches.
• Experience supporting testing, implementation and transition to business-as-usual, with attention to traceability, evidence and control requirements.
• Strong analytical and problem-solving skills, with the ability to work across complex data, process and technology landscapes.
• Ability to manage competing priorities, meet deadlines, make sound decisions and work independently while maintaining strong collaboration.
• Familiarity with data analysis, query, workflow or automation tools is desirable; practical knowledge of cloud technologies and modern data platforms would be an advantage.
• Excellent written and verbal communication skills, with the ability to present complex topics clearly to colleagues at different levels and across cultures.

Job Data by YubHub.

The successful candidate will take ownership of problems from investigation through resolution and be comfortable working across multiple teams and disciplines. The role requires switching rapidly between priorities, such as developing Python research tools or AI-enabled workflows, investigating complex data issues, validating investment analytics, or supporting research or client requests.

Key Responsibilities

• Develop, test, and maintain Python and SQL-based research tools, investment analytics, and data pipelines, applying strong software engineering and CI/CD practices.
• Perform detailed data analysis, validation, and quality assurance across large financial datasets; investigate anomalies and identify root causes across data, code, and methodology.
• Develop automation and AI-enabled tools and agents to improve research, data checking, and operational workflows.
• Support quantitative investment and index research, including factor analysis, regression, portfolio optimisation, risk modelling, and performance analytics.
• Work with datasets and platforms including Worldscope, IBES, Lipper, Datastream, and Refinitiv Workspace, developing a strong understanding of their structure, coverage, and appropriate application.
• Partner with Research Analysts, Engineering, Technology, and Data Operations to translate analytical requirements into robust, scalable solutions.
• Support index research, methodology development, rebalances, and other operational activities where strong analytical and technical expertise is required.
• Respond to internal and external analytical enquiries and contribute to client-facing analysis and materials.
• Continuously improve existing code, processes, and research infrastructure with a focus on scalability, automation, accuracy, and maintainability.

Candidate Profile

The ideal candidate will have approximately 5 years of experience in quantitative development, financial data analytics, quantitative research, or a related discipline, with strong hands-on Python and SQL skills. Experience with pandas, NumPy, Git, testing, CI/CD, cloud computing, and modern development environments such as VS Code and GitHub Copilot is highly desirable, as is practical experience developing with generative AI and AI agents.

Benefits

LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days, and wellbeing initiatives.

Job Data by YubHub.

Key responsibilities include:

• Developing and maintaining quantitative research, analytics and automation platforms
• Building AI-enabled workflows, tools and agents to improve research, operational efficiency and client support
• Supporting quantitative research initiatives, investment analytics and index methodology development across equity and multi-asset strategies
• Investigating and resolving complex data, analytics and operational issues while maintaining the highest standards of quality and accuracy
• Driving improvements in research infrastructure, development processes, CI/CD practices and cloud-based solutions
• Partnering closely with Research, Engineering, Technology, Product, Data Operations and Sales teams to deliver business objectives
• Providing analytical support and responding to internal and external enquiries relating to data, methodologies, analytics and product capabilities
• Contributing across the full lifecycle of research and product development, from idea generation and data validation through implementation, deployment and client-facing delivery

The ideal candidate will have approximately 10 years of experience spanning quantitative research, quantitative development, investment analytics or related disciplines. They will possess strong Python and SQL skills, experience with CI/CD, cloud computing, AI-assisted development tools and modern software engineering practices. A solid understanding of equity markets and quantitative investment techniques is essential.

LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.

Job Data by YubHub.

The successful candidate will take ownership of identifying, developing and converting growth opportunities across FTSE Russell's asset-based and data businesses. The position will cover multiple client segments, including asset managers, asset owners, banks, wealth managers, ETF issuers, insurers, investment consultants, trading firms, platforms and other financial-market participants.

The role spans two principal commercial areas:

• Asset-based business: index adoption and licensing associated with ETFs, index funds, mutual funds, institutional mandates, structured products, derivatives and other index-linked investment solutions.
• Data and subscription business: index and benchmark data, analytics, reference data, enterprise data rights and subscription-based solutions.

The Senior Sales Specialist will:

• Own and execute a comprehensive sales and business-development strategy for the DACH and CEE region, aligned with FTSE Russell's EMEA commercial priorities.
• Translate the regional strategy into a structured territory plan covering priority countries, client segments, target accounts, buyer groups and relevant propositions.
• Assess the total addressable market and identify areas where FTSE Russell has the strongest potential to generate sustainable asset-based and subscription revenues.
• Identify gaps in current market coverage and build a prioritised plan for new client acquisition, account penetration and expansion.
• Establish clear short-, medium- and longer-term priorities for the territory, balancing immediate revenue delivery with strategic market development.
• Develop senior-level relationships across the regional investment and financial-services ecosystem.
• Represent the requirements, commercial dynamics and evolving priorities of DACH and CEE clients within FTSE Russell.
• Provide regular market intelligence and recommendations to EMEA sales leadership, Product, Research and Marketing teams.
• Contribute to proposition development and go-to-market decisions by articulating regional client needs, competitive pressures and addressable opportunities.

The ideal candidate will have:

• Significant experience in institutional sales, business development, commercial relationship management or a closely related financial-markets role.
• A strong and demonstrable record of originating, developing and closing commercial opportunities.
• Relevant experience gained within an asset manager, bank, index provider, financial-data provider, investment consultancy, ETF business or comparable financial-services organisation.
• Strong understanding of financial markets, investment products and institutional client workflows.
• Experience developing a territory, client segment or business line with a meaningful degree of autonomy.
• Demonstrable experience managing complex sales cycles involving multiple client and internal stakeholders.
• Fluency in German and English, with the ability to lead sophisticated commercial discussions and negotiations in both languages.
• Willingness to travel regularly across Germany, the wider DACH market and CEE.

In return, the role offers a hybrid approach to workplace, with the opportunity to work across all parts of the enterprise, and a flexible work arrangement.

Job Data by YubHub.

The ideal candidate is a self-sufficient, technically excellent engineer who can lead through architectural clarity, thorough code review, and hands-on delivery. The role involves building low-latency, event-driven calculation engines, operating a cloud-native platform, and delivering secure APIs and streaming distribution.

Responsibilities:

• Build low-latency, event-driven calculation engines that price indices accurately through market events.
• Operate a cloud-native, horizontally scalable, always-on platform, built as resilient and managed through infrastructure as code.
• Own data foundations for real-time market and reference data, with strong modelling, quality and auditability.
• Deliver secure APIs and streaming, event-driven distribution that make real-time index data easy to consume.
• Help bring advanced and multi-asset methodologies to market.
• Modernise the operations experience: replace manual workflows with intuitive tooling and observability.
• Lead through architecture, code review and test strategy, partnering across product, operations and client-facing teams.

Tech Stack:

• Development: Java, C#, Python, SQL, OpenAPI
• Cloud: AWS (Lambda, API Gateway, S3, SQS, SNS, Aurora, and others as required)
• Databases: Sybase ASE, Sybase IQ, Aurora Postgres
• IaC and CI/CD: Terraform, AWS CLI, GitLab
• AI Development: Agentic AI tooling (e.g. GitHub Copilot, Claude Code)

Experience We Value:

• 9+ years of professional software engineering experience.
• Strong expertise in system design, distributed and event-driven systems, and relational data modelling.
• Solid experience building and operating cloud-native applications on AWS.
• Ability to write and maintain infrastructure as code (Terraform or equivalent).
• Experience designing test strategies at multiple levels of the testing pyramid.
• Proficiency with AI development tooling and a clear understanding of how to use AI to accelerate delivery while maintaining quality.
• Strong debugging skills across distributed systems.
• Basic understanding of financial services or capital markets.
• Effective collaboration and the ability to communicate technical decisions to non-technical audiences.

Benefits: LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.

Location: Bengaluru (Hybrid, 3 days/week in office)

Job Data by YubHub.

We build primarily in Python, so that's our preference , but depth of engineering judgement matters more to us than the language on your CV. If you've led the design and delivery of serious systems in Java, C#, C, C++, Scala, Go, or Rust and you're motivated to lead in Python, we'd like to talk. At this level we expect you to become fluent quickly and to bring the cross-language perspective with you.

This is a hands-on Lead IC role , not a management role. You'll still be writing and reviewing code every week. What changes at this level is scope: you own architecture and technical direction in a defined area, you mentor and grow the engineers around you, and you raise quality across the team through reuse, good design, and hands-on support. The systems handle serious volumes of financial data, so there's real depth in the data problems , but you're being hired as a software engineer who leads through code.

Responsibilities

• Staying hands-on , designing and writing production code, primarily in Python with 10 +yrs of experience , and setting the standard for what good looks like through the code you ship
• Owning technical direction and architecture for a defined area of the platform, and making the trade-offs explicit so the team can move fast with confidence
• Leading design of software systems , services, APIs, shared libraries, and the interfaces between them , with resilience, performance, and reusability designed in
• Driving engineering quality across the team: raising the bar in code review, reducing duplication through well-designed shared components, and championing testing, refactoring, and secure development practices
• Mentoring and coaching engineers , pairing, reviewing, and growing capability so that good practice outlives any one project
• Digging into design and risk trade-offs , failure modes, operational readiness, security, and cost , and resolving the blockers that slow the team down
• Designing data-intensive software across relational databases (Aurora PostgreSQL), object storage, and AWS services, with careful attention to schema design and evolution at scale
• Building software that processes data at scale on AWS , Lambda, containerised services, and where appropriate Glue, EMR Serverless, and lakehouse table formats such as Apache Iceberg
• Embedding observability and quality controls so issues are found before customers find them
• Influencing and collaborating across teams, and translating between technical and non-technical audiences
• Building deep knowledge of the financial indices domain and using it to guide team-level design

Requirements

• A substantial track record of building and shipping software. Applications, services, platforms, or libraries you designed, built, ran in production, and evolved over years , not just pipelines and scripts
• Python is our preference, but not a hard gate at this level either. Either you already lead in production Python, or you have equivalent depth in Java, C#, C, C++, Scala, Go, or Rust and are motivated to make Python your primary language here
• Depth in software design and architecture , you can decompose a complex problem, choose the right boundaries, and explain why
• You write and review excellent code. In Python: type hints, linters, strong pytest discipline, and an instinct for readable, maintainable code , and the equivalent rigour in any other language you've worked in
• You are genuinely hands-on and intend to stay that way. Leading through code is the point of this role
• Proven experience mentoring and levelling up other engineers , through code review, pairing, design guidance, and setting standards
• Strong ownership of technical outcomes , you take responsibility for what production does, not just what merges
• Deep experience with relational databases (e.g. Aurora PostgreSQL) , modelling, performance, and evolution under real load
• Solid AWS experience and strong CI/CD, automation, and testing practice
• Comfort with data-intensive systems , batch processing, ETL, schema evolution, and reasoning about correctness at volume
• Excellent communication , you tailor how you explain design decisions to technical and non-technical audiences and create shared understanding
• You value collaboration over solo heroics and thrive in Agile teams

Nice to Haves

• Apache Spark / PySpark and experience optimising large-scale distributed processing
• Big data experience , designing systems for datasets and workloads well beyond single-machine scale
• Breadth across languages used in data-intensive and performance-critical systems , Scala, Java, C++, Go, or Rust , and the judgement to know when reaching for one is warranted
• Apache Iceberg, Delta Lake, or similar open table formats, and lakehouse architecture
• Databricks, Snowflake, or comparable data platforms
• CI/CD tooling such as GitLab CI, Jenkins, or GitHub Actions
• Infrastructure as code (Terraform, CDK) and platform/DevOps exposure
• Data quality frameworks like Great Expectations or Deequ
• Experience in financial markets, index data, or investment analytics
• Experience in finance domain (investment banking, asset/portfolio management) or in any product company

Job Data by YubHub.

This role will provide core execution support across the issue lifecycle, helping to ensure that issues are accurately recorded, appropriately tracked, well evidenced and subject to timely follow-up. The role is central to maintaining high-quality issue data, supporting governance routines, and enabling clear management information on issue health, remediation progress, ageing and emerging risk themes.

Working as part of the 1LOD Risk & Control function, the Analyst will support the consistent application of Issue Management procedures and controls in line with LSEG standards. The role will work closely with Issue Owners, Action Owners, Risk & Control colleagues and governance stakeholders to help ensure that issue records are complete, remediation actions are visible, and closure evidence is captured in a clear and audit-ready manner.

Key Responsibilities

Issue Management Lifecycle Support

• Support the day-to-day operation of the Issue Management framework, including issue creation, tracking, remediation monitoring and closure preparation.
• Maintain accurate and complete issue records, ensuring key fields, ownership, ratings, dates, action plans and closure evidence are consistently captured.
• Assist with the triage and quality review of new and existing issues to ensure records meet required procedural and data quality standards.
• Track remediation actions and follow up with Issue Owners and Action Owners to support timely delivery and escalation of overdue items.
• Monitor issue ageing, due dates, delivery milestones and closure readiness, highlighting exceptions or emerging concerns to senior colleagues.
• Support the preparation of issue closure packs, including checking that evidence is complete, clearly referenced and aligned to agreed closure criteria.
• Help identify inconsistencies, gaps or incomplete information within issue records and work with stakeholders to resolve them.

Data Quality, Reporting and Management Information

• Perform regular data quality checks across issue management records, identifying missing fields, inconsistent ratings, unclear ownership or outdated action plans.
• Support production of routine Issue Management MI, including issue volumes, ageing, remediation status, overdue actions, closure trends and risk themes.
• Assist with analysis of issue trends, hotspots and systemic drivers to support better understanding of the risk and control environment.
• Help maintain dashboards, trackers and reporting packs used for governance forums and senior management updates.
• Ensure reporting outputs are accurate, reconciled and produced in line with agreed timelines and standards.
• Support continuous improvement of issue data quality, reporting definitions and MI production processes.

Governance and Stakeholder Support

• Support preparation for Issue Management governance meetings, including agenda preparation, meeting packs, action logs and follow-up tracking.
• Capture and maintain clear records of decisions, escalations and actions arising from governance forums.
• Liaise with Issue Owners, Action Owners and Risk & Control colleagues to gather updates, clarify remediation progress and support issue lifecycle discipline.
• Escalate data quality concerns, overdue actions or unclear ownership to senior team members in a timely and structured way.
• Support engagement with second line Risk, Compliance, Internal Audit and other stakeholders by helping to provide clear, accurate and well-organised issue information.

Control, Risk and Process Discipline

• Support the application of Issue Management procedures, controls and standards across FTSE Russell.
• Contribute to the maintenance of audit-ready records and evidence to support internal review, control testing and regulatory scrutiny.
• Help identify opportunities to simplify, standardise and improve issue management processes.
• Support alignment between issue records, incidents, controls, RCSA outcomes and remediation activity where relevant.
• Promote strong risk culture behaviours through attention to detail, transparency, timely escalation and disciplined follow-through.

Experience & Skills

Essential

• Strong analytical skills with the ability to review, organise and interpret large volumes of information.
• Excellent attention to detail and a strong focus on data quality, accuracy and completeness.
• Good Microsoft Excel skills, including the ability to maintain trackers, analyse data and support reporting outputs.
• Strong organisational and planning skills, with the ability to manage multiple deadlines and follow up on actions.
• Clear written and verbal communication skills, including the ability to summarise information accurately and professionally.
• Ability to work with stakeholders across different teams and levels of seniority to gather updates and resolve queries.
• Comfortable working with structured processes, governance routines and control requirements.
• Proactive mindset, with the ability to identify gaps, ask questions and escalate issues appropriately.
• Ability to operate in a fast-paced environment while maintaining accuracy and delivery discipline.

Desirable

• Experience in issue management, operational risk, governance, controls, audit support or management information production.
• Familiarity with MetricStream, Jira or similar workflow, risk, issue or governance tools.
• Understanding of risk and control concepts, including remediation planning, control weaknesses and closure evidence.
• Experience supporting governance forums, including meeting packs, action logs and reporting.
• Experience within financial services, market infrastructure, index, benchmark, data or analytics businesses.
• Awareness of regulated environments and the importance of clear evidence, audit trails and defensible documentation.

Job Data by YubHub.

The successful candidate will take ownership of problems from investigation through resolution and be comfortable working across multiple teams and disciplines. The role involves developing, testing, and maintaining Python and SQL-based research tools, investment analytics, and data pipelines, as well as performing detailed data analysis, validation, and quality assurance across large financial datasets.

Key responsibilities include:

• Developing, testing, and maintaining Python and SQL-based research tools, investment analytics, and data pipelines
• Performing detailed data analysis, validation, and quality assurance across large financial datasets
• Developing automation and AI-enabled tools and agents to improve research, data checking, and operational workflows
• Supporting quantitative investment and index research, including factor analysis, regression, portfolio optimisation, risk modelling, and performance analytics
• Working with datasets and platforms including Worldscope, IBES, Lipper, Datastream, and Refinitiv Workspace
• Partnering with Research Analysts, Engineering, Technology, and Data Operations to translate analytical requirements into robust, scalable solutions
• Supporting index research, methodology development, rebalances, and other operational activities
• Responding to internal and external analytical enquiries and contributing to client-facing analysis and materials
• Continuously improving existing code, processes, and research infrastructure with a focus on scalability, automation, accuracy, and maintainability

The ideal candidate will have approximately 5 years of experience in quantitative development, financial data analytics, quantitative research, or a related discipline, with strong hands-on Python and SQL skills. Experience with pandas, NumPy, Git, testing, CI/CD, cloud computing, and modern development environments is highly desirable.

LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days, and wellbeing initiatives.

Job Data by YubHub.