Primary responsibilities include:

• Owning independent risk oversight: overseeing global credit portfolios, with a clear view of exposures across credit spread, default, recovery, curve, basis, convexity, embedded optionality, ratings migration, financing, liquidity, and correlation.
• Analysing P&L and risk: analysing risk drivers, P&L attribution, hedging efficiency, scenario behaviour, and tail outcomes for portfolios trading corporate bonds (investment grade and high-yield), leveraged loans, credit indices (CDX, iTraxx), single-name CDS, tranches, and structured products such as CLOs and non-agency MBS.
• Developing and overseeing risk guidelines: establishing guidelines for portfolio construction, concentration, liquidity, gap risk, financing, and drawdown. Ensuring mandates are defined, scalable, and consistently observed.
• Reviewing trade and portfolio construction: reviewing positions with close attention to bond and loan terms, covenants, capital structure, seniority and security, structural protections, embedded optionality (calls, puts, prepayment and extension risk), CDS documentation, index and tranche construction, financing and margin assumptions, and event risk (ratings actions, refinancings, restructurings, and defaults).
• Reviewing portfolio risk: working closely with portfolio managers to assess positions where risk may be mispriced, crowded, imperfectly hedged, or less aligned with mandate, liquidity, or market regime, with particular focus on default and downgrade risk, complex structures, and crowded credit themes.
• Evaluating portfolio manager candidates: assessing prospective Portfolio Manager candidates by testing the strength of their process, risk discipline, hedging approach, portfolio construction, and historical returns.
• Improving risk infrastructure: enhancing the Firm's models, systems, and reporting for credit risk. Working with quantitative researchers and technologists to improve valuation, stress testing, exposure decomposition, default and loss modelling, and real-time reporting.
• Communicating with precision: presenting key exposures, stress results, and changes in market structure clearly to senior leadership and investment teams.
• Monitoring global market developments: tracking primary and secondary market activity, issuance trends, liquidity, market structure, rating migration, default cycles, and regional differences in the U.S., Europe, and Asia that may affect risk-taking and portfolio construction.

XML job scraping automation by YubHub

Primary responsibilities include:

• Owning independent risk oversight: overseeing global convertible bond portfolios, with a clear view of exposures across delta, gamma, vega, credit spread, rates, borrow, financing, liquidity, and correlation.
• Analysing P&L and risk: analysing risk drivers, P&L attribution, hedging efficiency, scenario behaviour, and tail outcomes.
• Developing and overseeing risk guidelines: establishing guidelines for portfolio construction, concentration, liquidity, gap risk, financing, and drawdown. Ensuring mandates are defined, scalable, and consistently observed.
• Reviewing trade and portfolio construction: reviewing positions with close attention to bond terms, embedded optionality, capital structure, stock borrow, dividends, corporate actions, financing assumptions, and event risk. Assessing both directional and relative-value risk.
• Reviewing portfolio risk: working closely with portfolio managers to assess positions where risk may be mispriced, crowded, imperfectly hedged, or less aligned with mandate, liquidity, or market regime.
• Evaluating portfolio manager candidates: assessing prospective Portfolio Manager candidates by testing the strength of their process, risk discipline, hedging approach, portfolio construction, and historical returns.
• Improving risk infrastructure: enhancing the Firm's models, systems, and reporting for convertible bond risk. Working with quantitative researchers and technologists to improve valuation, stress testing, exposure decomposition, and real-time reporting.
• Communicating with precision: presenting key exposures, stress results, and changes in market structure clearly to senior leadership and investment teams.
• Monitoring global market developments: tracking issuance, liquidity, market structure, and regional differences in the U.S., Europe, and Asia that may affect risk-taking and portfolio construction.

XML job scraping automation by YubHub

You will collaborate closely with technical teams to support the development and refinement of new AI capabilities, with a primary focus on quantitative financial risk management domains. Your expertise will drive the selection and rigorous resolution of complex risk-related problems, including market risk modeling, credit and counterparty risk, liquidity and funding risk, operational and model risk, stress testing & scenario analysis, Value at Risk (VaR)/Expected Shortfall (ES), risk attribution, capital allocation (economic/regulatory), and enterprise-wide risk frameworks under regulatory regimes (Basel, Dodd-Frank, IFRS 9, etc.).

This role requires exceptional quantitative rigor, rapid adaptation to evolving guidelines, and the ability to deliver precise, technically sound critiques, derivations, and solutions in a fast-paced environment. As a Finance Risk Expert, you will directly support xAI's mission by helping train and refine frontier AI models. You will teach the models how risk professionals quantify uncertainties, model tail events, assess portfolio vulnerabilities, ensure regulatory compliance, perform stress testing, and make data-driven decisions to protect capital and maintain financial stability.

Your tasks may include recording audio walkthroughs of risk models, participating in video-based scenario reasoning, or producing detailed quantitative risk analysis traces. All outputs are considered work-for-hire and owned by xAI.

Responsibilities:

• Use proprietary annotation and evaluation software to deliver accurate labels, rankings, critiques, and comprehensive solutions on assigned projects
• Consistently produce high-quality, curated data that adheres to strict quantitative and regulatory standards
• Collaborate with engineers and researchers to develop and iterate on new training tasks, risk-specific benchmarks, and evaluation frameworks
• Provide constructive feedback to improve the efficiency, precision, and usability of annotation and data-collection tools
• Select and solve challenging problems from financial risk domains where you have deep expertise

Basic Qualifications:

• Master’s or PhD in a quantitative discipline: Quantitative Finance, Financial Engineering, Financial Mathematics, Statistics, Applied Mathematics, Econometrics, Risk Management, Operations Research, Physics, Computer Science (with risk/finance focus), or closely related field or equivalent professional experience as a quantitative risk analyst, risk modeler, or risk quant
• Excellent written and verbal English communication (technical reports, regulatory documentation, explanatory breakdowns)
• Strong familiarity with financial risk data sources and platforms (Bloomberg, Refinitiv, Moody’s Analytics, S&P Capital IQ, RiskMetrics, internal bank risk systems, regulatory filings, Basel/FRB datasets, etc.)
• Exceptional analytical reasoning, attention to detail, and ability to exercise sound judgment with incomplete or ambiguous data

Preferred Skills and Experience:

• Professional experience in quantitative risk management, model development/validation, or risk analytics at a bank, hedge fund, asset manager, insurance company, regulator, or consulting firm
• Track record of publication(s) or contributions in refereed journals/conferences on risk, econometrics, statistics, or quantitative finance
• Prior teaching, mentoring, or training experience (university, industry workshops, regulatory training)
• Proficiency in Python/R for risk modeling (pandas, NumPy, SciPy, statsmodels, QuantLib, PyTorch/TensorFlow for ML risk models, etc.) and familiarity with risk systems (Murex, Calypso, Numerix, etc.)
• Experience with Monte Carlo simulation, copula models, stochastic processes, time-series analysis, extreme value theory, or machine learning for risk (anomaly detection, credit scoring, etc.)
• Knowledge of regulatory capital frameworks (Basel III/IV, FRB CCAR, SR 11-7 model risk guidance, IFRS 9/CECL, Solvency II)
• CFA, FRM, PRM, CQF, or similar risk-focused certifications
• Previous exposure to large language models, AI safety, or quantitative evaluation pipelines

Location and Other Expectations:

• Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit
• For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required
• Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs
• For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time
• We are unable to provide visa sponsorship
• For those who will be working from a personal device, your computer must meet xAI’s minimum hardware requirements

XML job scraping automation by YubHub

In this role, you will leverage your expertise in credit risk assessment and analysis, including financial statement analysis, credit risk modeling, covenant analysis, leverage and coverage ratio calculations, industry and company research, cash flow analysis, debt capacity assessments, credit memo preparation, counterparty risk evaluation, rating methodologies, credit monitoring, and risk mitigation strategies to support the training of AI systems.

You will collaborate with technical teams to refine annotation tools and curate impactful data, ensuring our models effectively capture real-world private credit analysis dynamics.

This role requires adaptability, strong analytical skills, and a passion for driving innovation in a fast-paced environment.

Responsibilities:

• Utilize proprietary software to provide accurate input and labels for private credit projects, ensuring high-quality data for AI model training.
• Deliver curated, high-quality data for scenarios involving financial statement analysis, credit risk assessment, covenant compliance evaluation, debt capacity modeling, industry benchmarking, cash flow projections, rating analysis, and credit monitoring activities.
• Collaborate with technical staff to support the training of new AI tasks and contribute to the development of innovative technologies.
• Assist in designing and improving efficient annotation tools tailored for credit analysis data.
• Select and analyze complex problems in credit analysis aligned with your expertise to enhance AI model performance.
• Interpret, analyze, and execute tasks based on evolving instructions, maintaining precision and adaptability.

Basic Qualifications:

• Professional experience in credit analysis or related fields (e.g., credit analyst, underwriter, or risk professional at commercial banks, investment banks, rating agencies, insurance companies, or corporate credit departments).
• Proficiency in reading and writing informal and professional English.
• Strong communication, interpersonal, analytical, and organizational skills.
• Excellent reading comprehension and ability to exercise autonomous judgment with limited data.
• Passion for technological advancements and innovation in credit analysis.

Preferred Skills and Experience:

• Relevant certification or advanced training (e.g., CFA, FRM, CRC or similar finance-related certification).
• Experience mentoring or training others in private credit practices, such as credit underwriting, loan structuring, covenant analysis, or portfolio monitoring.
• Comfort with recording audio or video sessions for data collection.
• Familiarity with AI or data annotation workflows in a technical setting.

Location and Other Expectations:

• Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit.
• For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.
• Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs.
• For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time.
• We are unable to provide visa sponsorship.
• For those who will be working from a personal device, your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.

Compensation and Benefits:

US based candidates: $45/hour - $100/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.

Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process.

XML job scraping automation by YubHub

Responsibilities:

• Develop scalable methods to identify, measure, and control end-to-end risks across the user lifecycle, including credit and fraud risks.
• Proactively identify risk management opportunities and outline the strategy, translating complex requirements into technical specifications.
• Work closely with Product, Engineering, and Data Science teams to shape new product offerings and develop data-driven, globally scalable systems and processes.
• Become an expert on the global ecosystem of Stripe's products, integrations, tools, and partner requirements, and how those elements interact with payment risks.
• Develop strong internal relationships across partner teams and challenge the payments industry status quo to enable innovative businesses to flourish online.

Requirements:

• 5+ years of relevant experience with financial risk modeling.
• A builder's mindset with a willingness to question assumptions and conventional wisdom.
• Analytical skills, with expertise in data analysis, modeling, and framing business decisions and tradeoffs effectively through quantitative analysis and visualization.
• Collaborative skills, with the ability to work effectively across teams and build strong working relationships.
• Decisive, yet open to learning, with the ability to make critical decisions and quickly learn and iterate from experiences.
• Experience with SQL required.
• Bachelor's degree in Economics, Statistics, Computer Science, Engineering, or other quantitative or related field.

XML job scraping automation by YubHub

The credit risk operations team is responsible for conducting credit risk assessments, underwriting small and mid-size users, and proposing mitigation strategies that enable Stripe to take smart risks for our users.

Responsibilities:

• Work with merchants to evaluate their business models and financial statements
• Help manage Stripe's portfolio by developing a deep understanding of risk across industries, geographies, and operating models
• Identify differing risks of complex business models and enforce appropriate loss mitigation actions based on your assessment
• Utilize analytics to optimize strategies which can be enforced across Stripe's portfolio
• Identify risk factors and trends and further report these identifiers to the wider risk team to ensure consistency in partnership
• Identify gaps in current systems, policies and strategies, and recommend enhancements and process improvements

Requirements:

• A minimum of 1+ years of experience with knowledge of commercial credit underwriting, financial risk modeling and cash flow forecasting
• Ability to transform business and financial data into a cohesive narrative that outlines potential credit risks
• Strong knowledge of accounting principles and comfort with evaluating financial statements and business models across a range of industries
• Analytical thinking and problem solving skills
• Process-oriented mindset and ability to get things done
• Ability to prioritize and enjoy working in a quick-moving environment
• Humble and proven track record for working well across teams and with external partners

Preferred qualifications include proficiency in SQL or other data analysis tools and the ability and desire to challenge the status quo.

XML job scraping automation by YubHub

Responsibilities:

• Work directly with our top merchants to evaluate their business models and financial statements
• Provide tailored credit risk recommendations that mitigate Stripe's exposure, while facilitating partner company growth
• Help manage the portfolio by developing a deep understanding of risk across industries, geographies, and operating models
• Deliver insights to support senior management decisions, ranging from onboarding strategies to merchant pricing analysis
• Support the refinement of tools and processes to help the team deliver on key performance indicators, such as credit loss targets or portfolio coverage metrics
• Work with internal and external partners to support merchants around the world

Requirements:

• 3+ years of relevant experience with knowledge of commercial credit underwriting, financial risk modeling, and cash flow forecasting
• Bachelor's degree in Finance, Economics, Statistics, or other related fields
• Strong knowledge of accounting principles and comfort evaluating financial statements and business models across a range of industries
• Ability to transform business and financial data into cohesive narratives that outline potential credit risks and present dynamic mitigation strategies
• Strong written, verbal, and analytical skills
• Attention to detail while managing priorities in a fast-paced environment
• Ability to comfortably interact with the CFOs and CEOs of our top merchants
• Deep empathy for entrepreneurs running a business, and are motivated to solve problems to empower them

Preferred Qualifications:

• Strong technical expertise, including demonstrated experience with SQL
• Strong data visualization skills and a passion for data and analysis
• Experience working in tech, or other fast-paced, high-growth environments

XML job scraping automation by YubHub

This role involves analysing business and regulatory requirements to ensure compliance with local and international insurance regulations. You will assist in the preparation of financial reports, ensuring accuracy and timeliness in delivery. Your contributions will support the implementation of regulatory frameworks and promote the establishment of best practices across financial reporting processes.

Our client is one of the largest insurance companies globally, known for its scale and commitment to excellence.

Key Responsibilities:

M&A Due Diligence & Audits

• Lead financial due diligence for insurance acquisitions and strategic partnerships.
• Manage large-scale on-site and remote audits, evaluating underwriting performance, claims reserves, and financial stability.

Accounting & IFRS (Including IFRS 17)

• Oversee implementation and compliance with IFRS 17 and related standards for statutory reporting.
• Identify and optimise accounting processes to ensure efficient booking flows and reduce manual interventions.

Risk Management & GRC (Insurance-Focused)

• Develop and refine Governance, Risk, and Compliance (GRC) frameworks aligned with regulatory bodies such as Solvency II.
• Monitor risk exposure across underwriting portfolios, claims, and reinsurance contracts.

Controlling & Reporting

• Supervise budgeting, forecasting, and variance analysis across Life, Non-Life, and Reinsurance lines.
• Design and deliver executive dashboards to communicate financial performance, claims ratios, and reserve adequacy.

Requirements

Qualifications:

• Financial Expertise

+ Proven experience in financial due diligence, audits, IFRS compliance, and controlling within the insurance sector. + Strong understanding of Solvency II, capital adequacy, and risk modeling.

• Analytical Tools & BI

+ Hands-on experience with BigQuery or similar data platforms. + Proficiency in dashboard creation tools (e.g., Power BI, Tableau) to generate actionable insights.

• Project Management & Leadership

+ Demonstrated success in managing cross-functional teams and facilitating stakeholder workshops. + Strong report writing, presentation, and communication skills.

• Professional Qualifications

+ CFA (completed or in progress); certifications such as CERA or other insurance risk credentials are a plus. + Deep knowledge of IFRS 17 and Solvency II frameworks

Benefits

Competitive compensation and benefits package:

1. Competitive salary and performance-based bonuses
2. Comprehensive benefits package
3. Career development and training opportunities
4. Flexible work arrangements (remote and/or office-based)
5. Dynamic and inclusive work culture within a globally renowned group
6. Private Health Insurance
7. Retirement Benefits
8. Paid Time Off
9. Training & Development
10. Performance Bonus

Note: Benefits differ based on employee level.

XML job scraping automation by YubHub

Location

San Francisco

Employment Type

Full time

Department

Data Science

Compensation

• $255K – $490K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance related bonus for eligible employees and benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick and safe time (1 hour per 30 hours worked)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

About the Team

Integrity Data Science sits at the centre of OpenAI’s mission to deploy powerful AI responsibly. We help ensure people can trust our products by building measurement systems, experimentation practices, and detection/mitigation strategies that protect OpenAI and our users from misuse, fraud, and evolving adversarial behaviours.

As the scope and urgency of Integrity work expands across product surfaces and go-to-market motion, we’re hiring a dedicated Data Science Manager to scale the team, strengthen execution across multiple Integrity domains, and deepen partnership with Product, Engineering, Operations, and adjacent orgs (e.g., Growth, Ads).

This role is based in our San Francisco HQ (in-office).

About the Role

As Data Science Manager, Integrity, you will lead a team of data scientists working across trust & safety, fraud prevention, risk analysis, measurement, and modeling. You’ll be accountable for building a high-performing DS function that can keep pace with fast-moving threats—and for shaping the analytical strategy that informs how OpenAI detects, measures, and mitigates integrity risks at scale.

This is a highly cross-functional leadership role. You’ll help set the roadmap with Integrity Product/Engineering leaders, evolve team structure and operating rhythms, raise the bar on technical rigor (experimentation, causal inference, modeling, metrics), and develop a culture of proactive, high-leverage impact. Many of the challenges in this space are emergent—new misuse patterns appear as the technology and ecosystem evolves—so this role requires strong judgment, comfort with ambiguity, and an ability to build systems that scale.

In this role, you will:

• Lead and scale a high-impact Integrity Data Science team—hiring, coaching, and developing DS ICs (and potentially future managers) while setting a strong technical and cultural bar.

• Drive strategy across multiple Integrity domains (policy enforcement, bot detection, fraud prevention, IP theft, risk measurement, abuse prevention), balancing near-term response with durable systems.

• Build and institutionalize analytical rigor: clear metric frameworks, experimentation standards, monitoring/alerting, and repeatable evaluation approaches for Integrity interventions.

• Partner deeply with Product & Engineering to shape roadmaps, prioritize the right bets, and translate ambiguous risk signals into practical product and platform decisions.

• Evolve team structure and operating model as the org scales—defining ownership boundaries, improving processes, and creating leverage through better tooling and AI-assisted workflows.

• Enable cross-org outcomes, supporting partners outside Integrity (e.g., Growth, Ads, GTM) where integrity risks intersect with product and business goals.

• Communicate clearly with senior leadership, synthesizing complex tradeoffs, surfacing risk, and driving alignment on priorities and success metrics.

• Push the team toward an AI-leveraged operating mode, using modern tooling and model capabilities to accelerate detection, triage, analysis, and iteration.

You might thrive in this role if you:

• Have deep experience leading and scaling Data Science teams, ideally in trust & safety, fraud/abuse, security, risk, or other adversarial problem spaces in fast-moving environments.

• Bring strong technical grounding across modern DS techniques (experimentation, causal inference, anomaly detection, risk modeling, measurement design) and can coach others to execute with rigor.

• Have a track record of building durable partnerships across DS, Engineering, Product, and Operations—able to influence without authority and create shared accountability.

• Are excellent at hiring, mentoring, and developing technical talent, and can build a culture that is both high-bar and supportive.

• Can translate messy, evolving threats into clear frameworks, metrics, and decisions—

XML job scraping automation by YubHub