Quantitative Analytics jobs at Jpmorgan in United States, New York

Job Responsibilities

• Discover and document data lineage to trace the end-to-end data journey from point of creation to consumption to support regulatory requirements, e.g. BCBS 239
• Partner with operations, technology and product organizations to document and challenge data controls across the data lineage for critical data flows
• Build strong partnerships across CIB Payments and corporate functions to support data related efforts
• Accelerate data analysis and issue resolution through effective program governance, process/data mapping and data deep-dives
• Support the adoption and implementation of Data Owner and Data Governance roles and responsibilities, as needed
• Effectively coordinate across multiple teams & levels to expedite complex deliverables

Required qualifications, capabilities, and skills

• 3+ years of experience at a leading investment bank
• Strong understanding of data governance, data quality, data lineage and metadata management concepts
• Experience in driving/managing successful projects and programs focused on data quality, data lineage, data controls, metadata management
• Excellent communication, presentation (both oral and written) & influencing skills - candidate will be dealing with stakeholders of varying degrees of seniority across Corporate/Firmwide, Finance, Risk, Compliance, Operations and Technology teams
• Strong metrics driven mindset to track progress, drive action and communicate and manage effectively
• Basic understanding of the company's business practices and familiarity with the company's products and services

Preferred qualifications, capabilities, and skills

• Experience in Program Management, Data Quality or Control organization within an investment bank or large financial services firm
• Experience in producing PowerPoint presentations for senior audiences
• Experience in the Payments domain at an Investment Bank

As a Product Finance & Business Manager in CIB Payments, you will collaborate with our senior product managers to build financial plans, monitor performance, and drive productivity agendas. Your role involves overseeing forecasting processes, organizing business reviews, and providing executive-level presentations. You will also ensure alignment with Payments strategy and develop multi-year business cases, objectives and key results.

Job Responsibilities:

• Partner with senior product and technology managers to build financial plans and conduct variance analysis.
• Oversee forecasting processes and measure results against objectives.
• Assist in communicating year-on-year spend and multi-year planning.
• Deliver executive-level presentations on strategy, budget, and project delivery.
• Drive large-scale productivity agendas and identify cost-saving opportunities.
• Organize required reporting for business review sessions.
• Develop multi-year staffing plans and drive location strategy.
• Provide oversight of the team’s strategic agenda and 6-quarter planning.
• Deliver management information reports on expense, delivery, and governance.
• Track and communicate the status and achievements of the technology group.
• Partner across Payment & Finance to develop improved processes and business solutions.

Required Qualifications, Skills, and Capabilities:

• Bachelor’s degree in Business, Finance, Economics, or related area.
• Experience in Financial Services Business Management with a strong financial management background.
• Highly motivated self-starter with excellent project management and organizational skills.
• Advanced skills in Microsoft Office and PowerPoint.
• Excellent presentation skills with the ability to present to senior and global business heads.
• Strong analytical and critical thinking skills with the ability to analyze large data sets.
• Excellent people skills with the ability to forge strong relationships and influence across functions.
• Proficient in Microsoft PowerPoint with a strong ability to create visually appealing and professional presentations.
• Demonstrated experience in synthesizing complex data from multiple sources into clear, concise, and compelling narratives.
• Ability to design and organize presentation content to effectively communicate key messages and insights.
• Experience in collaborating with cross-functional teams to gather and interpret data inputs for presentation development.

Preferred Qualifications, Skills, and Capabilities:

• Familiarity with P&L and portfolio governance tools to manage investments and business cases.
• Familiarity with Microsoft tools and Tableau.
• Knowledge of Payments, Data, & AI products and capabilities.

As a Quantitative Researcher- Alpha Quant in the Cash Equities team, you will focus on data processing, signal feature construction, signal research, and systematic trading. You will help to drive the alpha research agenda for central risk book trading, using data analytics and programming to drive business transformation. Your role will involve feature engineering from various data sources, building robust alpha calibration and attribution framework, portfolio optimization, develop prediction models, collaborating with trading desks and implementing trading strategies.

Job Responsibilities:

• Work closely with trading to build end-to-end design and implementation of daily and intraday signal research infrastructure, with special focus on central risk trading.
• Contribute from idea generation to production implementation: perform research, design prototype, implement signals, alpha calibration, and trading strategies, support their daily usage, and analyze their performances.
• Develop robust portfolio optimization framework including drawdown management for signal weighting and maximizing various utility functions.
• Research on factor models driving the cash and vol markets; Analyze factors and strategy performance under different market regimes.
• Develop models for market making taking into consideration fundamental and quantitative features, and historic behavior using statistics, machine learning or heuristics.
• Work with the business on risk recycle, alpha capture, and devise hedging strategies accordingly.
• Collaborate broadly with QR teams across regions to build reusable research libraries and tools to back testing and alpha attributions.

Required Qualifications, Capabilities, and Skills:

• You have a strong quantitative background, as well as practical problem-solving skills.
• You have direct working knowledge of signal research with market data and other financial data, alpha capture, risk warehousing, preferrable in equities.
• You like working closely with trading desks, understanding their business, and have a strong mind-set of ownership to have an impact on the way they operate.
• You demonstrate proficiency in code design and programming skills, with primary focus on Python, KDB, C++ or Java in a commercial environment.
• You have practical data analytics skills on real data sets gained through hands-on experience, and can handle and analyze complex, large scale, high-dimensionality data from various sources.
• You quickly grasp business concepts outside immediate area of expertise and adapt to rapidly changing business needs.
• You think strategically and creatively when faced with problems and opportunities. You always look for new ways of doing things.
• Your excellent communication skills, both verbal and written, can engage and influence partners and stakeholders.

Preferred Qualifications, Capabilities, and Skills:

• Strong graduate degree (MS or PhD) in a quantitative field (Computer Science, Financial Engineering, Mathematics, Physics, Statistics, Economics, …).
• Strong expertise in statistics and machine learning in financial industry.
• Robust testing and verification practice.
• Direct Experience with electronic trading, and knowledge of trading algorithms.
• 3 to 5 years’ experience in finance: market making, electronic trading, , trading strategies (high to low frequency: market making, statistical arbitrage, option trading…), or derivatives pricing and risk management.

Knowledge of equity and volatility products is a plus, but not strict r

As an Technology Audit Director within our Chief Data & Analytics Office Audit team, you will be responsible for managing and leading Audit’s Technology Risk Area/Domain coverage, including management of an audit plan, oversight and execution of audit activities, validation of audit issues, regulatory coordination and completion of continuous monitoring activities, including engagement with senior stakeholders. The Technology Audit Director will also be responsible for managing a team of auditors across varying levels. This role also involves supporting the Data Risk Management and Artificial Intelligence Subject Matter Expert functions across the Internal Audit Department.

Job responsibilities

• Develop and execute an annual audit plan with a variety of audit activities and manage planning and resourcing.
• Manage large and complex audit deliverables from planning to reporting, and produce quality deliverables to both department and professional standards.
• Review audit work in accordance with department and professional standards, and complete assignments in an efficient manner.
• Oversee all aspects of audits including risk assessments, audit planning, audit testing, control evaluation, report drafting and follow up and verification of issue closure.
• Finalize and communicate audit findings and use judgment to provide an overall opinion on the control environment.
• Build and maintain relationships with AMDP senior stakeholders, establishing a culture of engagement whilst adding value.
• Actively participate in key governance forums (e.g., Technology Control Forums) to provide independent challenge to management on control matters.
• Understand the stakeholder priorities and provide independent feedback on control enhancements/implementation.
• Effectively manage and lead the Audit team, performing timely review of work performed and providing honest and constructive feedback to proactively manage performance and enhance skills across the team. Understand the team’s strengths and areas of development and guide the team in achieving their individual goals whilst giving them opportunities to enhance their skills.
• Work closely with business and technology audit colleagues to ensure that key risks are identified and assessed in the program of audit coverage.
• Manage regulatory coordination for CDAO related risks especially during regulatory examinations and other activities.

Required qualifications, capabilities and skills

• 10+ years of technology internal or external auditing experience.
• Bachelor's degree (or relevant financial services or technology experience).
• Solid understanding of technology risk concepts, artificial intelligence, coding, data analytics and/or distributed technologies and internal control concepts with the ability to evaluate and determine the adequacy of controls by considering business and technology risks in an integrated manner.
• Advanced analytical skills, particularly in regard to assessing the probability and impact of an internal control weakness.
• Excellent verbal and written communication skills with the ability to present complex and sensitive issues to senior management, and influence change.
• Proven ability to develop and maintain professional relationships with key stakeholders.
• Ability to work effectively within a team, both locally and globally, share information, support colleagues and encourage participation.
• Proven ability to implement long-term enhancements across different areas within the firm by leading and actively participating in departmental working groups.
• Related professional certification such as CISA, CISSP, CIA etc.

Preferred qualifications, capabilities and skills

• Degree and background in Technology, Data or Artificial Intelligence.
• Prior experience with internal audit department in financial services industry or Big 4 accounting firms covering technology risks and controls.

Job Summary:

As a Vice President in the Quantitative Research SPG team, you will play a pivotal role in supporting the Global Securitized Product Group (SPG) business. Your responsibilities will include leading the development, documentation, and enhancement of advanced quantitative models and analytical tools for SPG. You will collaborate with the business, risk, and model review teams to support proper model usage, maintain infrastructure, and provide expert guidance and training to users and clients.

Job Responsibilities:

• Lead the development and maintenance of advanced models for valuation, risk assessment, profit and loss (P&L) calculations, as well as algorithms for quoting and market making, utilizing sophisticated mathematical approaches.
• Ensure comprehensive documentation of all new models to comply with firm-wide model risk policies and procedures.
• Design and implement analytical tools to monitor market conditions in Residential Mortgage-Backed Securities (RMBS), enhancing decision-making processes.
• Conduct data queries and processing for RMBS prepayment and credit modeling, ensuring high-quality data analysis at the loan or facility level.
• Investigate and develop new techniques to improve mathematical and computational efficiency within modeling processes.
• Ensure appropriate model usage across a diverse range of business users and risk functions, providing guidance and training as needed.
• Build and optimize a robust platform for large-scale data analysis to support various modeling initiatives.
• Develop a new model library focused on achieving desired computational efficiency and usability.
• Oversee the maintenance and enhancement of existing infrastructure used for valuing and hedging financial transactions.
• Work closely with risk and model review groups to ensure proper model usage, conduct model reviews, and implement effective risk controls.
• Provide support to internal and external clients regarding their model usage, addressing inquiries and facilitating training as needed.

Required qualifications, capabilities, and skills:

• 3+ years of experience at the Vice President level.
• Proficient in Python and C++ for developing analytical tools and models.
• Skilled in working within a Linux shell environment, utilizing shell scripting for automation and data processing.
• Extensive experience in data analysis focused on mortgage and loan performance datasets, specifically analyzing prepayment and credit historical data at the loan or facility level.
• Expertise in developing econometric models to assess financial performance and risk.
• Proficient in conducting Monte Carlo simulations for risk analysis and forecasting.
• Experienced in developing logistic regression models to predict binary outcomes based on historical data.
• Knowledgeable in developing factor models, including Principal Component Analysis (PCA) and hazard rate models.
• Proficient in using statistical Python packages such as NumPy, Pandas, and StatsModels for data manipulation and statistical analysis.

Job Responsibilities:

• Participate in the development of J.P.Morgan systematic trading strategies with our Structuring teams
• Develop, deploy, and maintain new and existing algorithmic trading strategies
• Expand and support the risk management platform used by traders to hedge investable indices traded with our clients
• Build foundational infrastructure to support new product offerings, enhance efficiency, and improve controls
• Provide support to Trading teams through risk analysis and investigations of production trading strategies
• Contribute to our automation ecosystem by delivering end-to-end automation and optimization of trading execution and other related investable index trading and risk management workflows

Required qualifications, capabilities, and skills:

• You hold an advanced degree (Master’s or PhD) in a quantitative field: Mathematics, Computer Science, Physics, Engineering (or equivalent)
• You have experience working with quantitative investment strategies and derivatives, ideally with cross-asset exposure to Equities, Commodities, and/or Rates
• You have a strong programming background with high proficiency in Python
• You have highly-focused attention to details and to the quality of deliverables
• You understand advanced mathematics used in financial modeling including topics such as calculus, numerical analysis, optimization, and statistics
• You have a good understanding of the mathematics involved in the valuation of financial products and trading strategies
• You demonstrate exceptional analytical, quantitative, and problem-solving skills
• Your excellent communication skills, both verbal and written, can engage partners and stakeholders on complex and technical topics, which you can explain with exceeding clarity

Preferred qualifications, capabilities, and skills.

• Experience of financial markets and familiarity with general trading concepts and terminology
• Knowledge of derivatives pricing theory, trading algorithms, and/or financial regulations
• You understand the different types of financial risk and you can discuss in detail ways of managing these risks
• You are interested in applying agile development practices in a front-office trading environment
• You have good practical knowledge of derivatives pricing and risk management of vanilla options and volatility products
• A mindset of robust system and solution design and implementation, including diligent testing and verification practices