At a Glance
- Tasks: Build and support data pipelines for systematic equities trading using Python.
- Company: Join JPMorgan Chase, a global leader in financial services.
- Benefits: Competitive salary, diverse culture, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and collaboration.
- Why this job: Make a real impact in the fast-paced world of trading technology.
- Qualifications: Strong Python skills and experience in quantitative trading systems.
Be an integral part of a technology team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products. As a Python Quant Data Engineer you will help build the technology for Systematic Equities Trading Business. The role would sit in the Equities Trading Data & Analytics technology team. As a Vice President Software Engineer at JPMorgan Chase within the agile technology team, you will play a crucial role in improving, developing, and delivering top-tier technology products in a secure, stable, and scalable manner. Your skills and contributions will have a substantial impact on the business, and your profound technical expertise and problem-solving methodologies will be utilized to address a wide range of challenges across various technologies and applications.
Job Responsibilities
- Build and support fast, reliable, globally consistent data pipelines (data ingestion, cleaning, backfilling, storing) for the research and execution systems ensuring data integrity and low-latency access for research and trading.
- Work with the research and trading teams to onboard new datasets efficiently and consistently for use globally by the business.
- Design and build robust tools and frameworks to support quantitative research and production trading.
- Design, build and support research infrastructure (e.g. data access APIs, high performant and scalable simulation environments, feature and strategy signal stores).
- Build and support research and trading analytics libraries (e.g. markouts, strategy analytics).
- Serve as a function-wide subject matter expert in one or more areas of focus.
- Actively contribute to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle.
- Influence peers and project decision-makers to consider the use and application of leading-edge technologies.
Required Qualifications, Capabilities, And Skills
- Design and implementation of front-office systems for quant trading.
- Hands-on practical experience delivering system design, application development, testing, and operational stability.
- Strong expertise in Python. Comfortable with scientific & dataset libraries such as pandas, numpy.
- Experience with KDB/Q.
- Knowledge of data pipelines, market data processing and backtesting workflows.
- Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines.
- Ability to tackle design and functionality problems independently with little to no oversight.
- Proficiency in automation and continuous delivery methods.
- In-depth knowledge of the financial services industry and their IT systems.
- Academic experience in Computer Science, Computer Engineering, Mathematics, or a related technical field.
- Knowledge of machine learning, statistical techniques and related libraries.
Preferred Qualifications, Skills And Capabilities
- Strong knowledge and experience in FIX, Market Data, Analytics, OMS, and equities trading in global markets are assets.
- Additional knowledge of Java / C++ is a strong plus.
- Practical cloud native experience is a plus.
- Practical cloud experience is a plus.
Python Quant Data Engineer - Systematic Trading Technology employer: JPMorganChase
At JPMorgan Chase, we pride ourselves on being a leading employer in the financial services sector, offering a dynamic work environment that fosters innovation and collaboration. As a Python Quant Data Engineer, you will be part of an agile technology team dedicated to developing cutting-edge solutions for systematic trading, with ample opportunities for professional growth and skill enhancement. Our commitment to diversity and inclusion ensures that every employee's unique talents are valued, making it an exciting place to build a rewarding career.
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We think this is how you could land Python Quant Data Engineer - Systematic Trading Technology
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We think you need these skills to ace Python Quant Data Engineer - Systematic Trading Technology
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Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
