The Portfolio Simulation Research team is building out a new engine for the joint simulation of the global macro economy, drivers of financial markets, individual assets, and private cashflow. The team is building and connecting innovative frameworks and approaches across these spaces in a Bayesian framework.

Responsibilities for this team include:

• Doing theoretical research to come up with new, or find existing models and methodologies in the risk space, across multiple asset classes including private assets.

• Doing empirical research to calibrate new models to financial data.

• Backtesting, documenting, and guiding new models and methodologies through validation.

• Connect with internal and external clients to identify industry-wide quantitative problems and collaborate with academics affiliated with BlackRock to explore solutions.

• Collaborate on papers for publication, presenting original research at industry conferences, and speaking with institutional clients about relevant research.

Additional job responsibilities may include working with portfolio management teams on custom projects supporting their investment processes or working with financial advisory teams on modeling projects for specific products.

The ideal candidate will have a PhD or equivalent experience in Mathematics, Statistics, Econometrics, Finance, Science, Economics, or other relevant quantitative fields, with 5 to 10 years of experience in quantitative modeling and analytics. They should have a proven track record of conducting high-quality empirical research or theoretical research relevant for empirical analysis, knowledge of financial mathematics (derivatives pricing), and experience with Bayesian or machine learning.

The successful candidate will be able to communicate quantitative information and collaborate optimally in a team environment, and have solid programming skills in Python and a drive and ability to quickly pick up new technologies.

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In this role, you will work closely with the business to gather and synthesise requirements, analyse data dependencies, and create project plans. You will also be responsible for managing day-to-day project deliverables, highlighting and escalating issues, and resolving conflicts and roadblocks.

Key responsibilities include:

• Working with the business to gather and synthesise requirements across both investment teams and core business asks
• Analysing upstream/downstream data dependencies and creating the necessary BRD/FRD, JIRA, and project plans
• Managing day-to-day project deliverables; highlighting, escalating, and resolving issues, conflicts, and roadblocks
• Creating user guides and other documentation that will be used to onboard new users to the platform
• Creating and maintaining product roadmaps and other project artifacts required to manage stakeholder expectations
• Coordinating/ tracking development tasks, testing, and verifying releases to ensure user requirements are being met

Required skills include subject matter expertise in Equities Derivatives, working knowledge of Equities Derivatives market data, pricing, and risk management methodologies, hands-on BA/PM experience working on proprietary derivatives pricing, analytics, and risk management systems, and high-level understanding of Asia Equities Options markets and requirements around listed options execution infrastructure.

Qualifications include 6+ years of experience in a relevant BA/PM role, experience working in a scrum environment, working knowledge of JIRA, development background or CFA, and basic understanding of Python and ability to read Java code to extract what is developed.

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Your primary responsibilities will include:

• Preparing performance attribution reports for senior management and portfolio managers, highlighting primary PnL drivers and providing ad-hoc deep-dive analysis as required.
• Investigating and explaining material PnL moves on a Trade Date and T+1 basis, acting as a key point of contact for traders, risk, and finance on all PnL-related queries.
• Developing systematic controls to validate and enhance PnL attribution processes, including automated reconciliations, threshold-based alerts, and exception reporting.

In addition, you will be responsible for monitoring and validating real-time and end-of-day pricing for all fixed income instruments across Rates, Credit, and FX, including derivatives and structured products.

You will also maintain a strong working knowledge of Greeks-based risk sensitivities and their application to PnL attribution across fixed income derivatives, collaborate with quants and risk teams to ensure risk factor decompositions used in PnL attribution are accurate and aligned with the firm's pricing and risk models, and support the testing and validation of new pricing models and their impact on PnL and risk reporting.

To succeed in this role, you will need to have an advanced degree in a quantitative discipline such as Engineering, Mathematics, Physics, Financial Engineering, or a related field, experience in PnL attribution, derivatives pricing/valuations, quantitative risk, or a closely related function within a front-office, risk, or portfolio analytics environment, and knowledge of fixed income products and their risk profiles across Rates, Credit, and FX, including derivatives, structured products, and asset-backed securities.

You will also need to have solid coding skills in Python, with the ability to work efficiently with large datasets, build automation, and develop analytical tools, and excellent communication skills, with the ability to interact effectively with portfolio managers, quants, risk, and technology teams across the firm.

If you are a collaborative team player with a strong willingness to support others, adapt quickly, and thrive in a fast-moving, high-pressure environment, we encourage you to apply for this exciting opportunity.

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Your primary responsibilities will include working with our salesforce to design an innovative product roadmap, as well as the actual products, to meet new or future client demand. You will also be responsible for helping to design compelling marketing campaigns around these products to maximise engagement with our client base.

In addition, you will oversee the full spectrum of product launch, including onboarding into our systems, to ensure risks generated by these products are well controlled by our organisation. You will liaise with our relevant trading teams to incorporate feedback, leverage our strengths, and plan out necessary future capabilities.

Collaboration with our internal tech teams will be essential to streamlining the trade volumes resulting from our equity derivatives and QIS businesses.

This is a full-time position, Monday to Friday, 40 hours per week, with a salary range of $250,000.00 to $260,000.00 per year.

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This position demands a dynamic approach to learning and adapting in a fast-paced environment, where your ability to interpret and execute tasks based on evolving instructions is crucial. As a Quantitative Finance Expert, you will play an essential role in advancing xAI's mission by supporting the training and refinement of xAI’s AI models. Quantitative Finance Experts teach our AI models about how people interact and react, as well as how people approach issues and discussions in quantitative finance. To accomplish this, Quantitative Finance Experts will actively participate in gathering or providing data, such as text, voice, and video data, sometimes providing annotations, recording audio, or participating in video sessions.

Responsibilities:

• Use proprietary software applications to provide input/labels on defined projects.
• Support and ensure the delivery of high-quality curated data.
• Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.
• Interact with the technical staff to help improve the design of efficient annotation tools.
• Choose problems from quantitative finance fields that align with your expertise, focusing on areas like portfolio optimization, derivatives pricing, or high-frequency trading backtests, providing rigorous solutions and model critiques where you can confidently provide detailed solutions and evaluate model responses.
• Regularly interpret, analyze, and execute tasks based on given instructions.

Basic Qualifications:

• Must possess a Master's or PhD in a quantitative finance-related field (Quantitative Finance, Financial Engineering, Financial Mathematics, Applied Mathematics, Statistics, Economics with quantitative focus, or related disciplines) or equivalent professional experience as a quantitative trader or analyst.
• Proficiency in reading and writing, both in informal and professional English.
• Strong ability to navigate various financial information resources, databases, and online resources (e.g., Bloomberg, Reuters, SEC filings).
• Outstanding communication, interpersonal, analytical, and organizational capabilities.
• Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material.
• Strong passion for and commitment to technological advancements and innovation in quantitative finance.

Preferred Skills and Experience:

• Professional experience as a quantitative trader or analyst.
• Possesses experience with at least one publication in a reputable finance or economics journal or outlet.
• Teaching experience as a professor
• Familiarity with Python/R for financial scripting or ML libraries (e.g., QuantLib)
• FRM (Financial Risk Manager)
• CQF (Certificate in Quantitative Finance)
• PRM (Professional Risk Manager)
• CAIA (Chartered Alternative Investment Analyst)
• CFA (Chartered Financial Analyst)

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