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- Tasks: Design and enhance market risk time series infrastructure using Snowflake and AWS.
- Company: Join a leading firm in risk technology with a global impact.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a difference in risk management while working with cutting-edge technologies.
- Qualifications: Experience in Python, SQL, and market risk concepts required.
- Other info: Collaborative environment with strong focus on innovation and career development.
The predicted salary is between 48000 - 72000 £ per year.
The Risk Technology group builds and supports a global risk platform enabling the Risk Management group to oversee all areas of risk across the Firm. The risk platform provides capabilities for measuring, quantifying, analyzing, reporting, and controlling exposures across market and credit.
The position is for a Techno-Functional Developer to design, enhance, and maintain the Market Risk Time Series infrastructure built on Snowflake and AWS. This role requires strong technical skills combined with deep domain expertise in market risk, including VaR, end-of-day market data, and historical time series. The candidate will work closely with the Market Data team and Risk stakeholders to ensure accurate, scalable, and auditable data solutions for risk analytics.
Primary Responsibilities:
- Data Sourcing & Integration: Source historical market data from multiple internal and external providers. Integrate with quant libraries to identify data quality issues and validate risk inputs.
- Data Quality & Remediation: Integrate with Quant APIs to detect and remediate common data quality issues (gaps, stale data, outliers, misalignments). Implement algorithms for gap-filling, back-filling, and anomaly correction to ensure data is fit for VaR and SVaR calculations.
- Infrastructure Development: Build and enhance Snowflake-based time series infrastructure for scalability and performance. Develop Python ETL/ELT pipelines and optimized SQL models for historical time series storage and retrieval.
- Collaboration & Governance: Work closely with Market Data and Risk teams to define canonical market observables and maintain data lineage. Ensure reproducibility and auditability of risk inputs for regulatory compliance.
Essential Experience/ Skills:
- + years of hands-on experience in developing applications using Relational Databases and Big-data platforms.
- Technical: Strong Python (pandas, numpy, data engineering best practices). Advanced SQL and Snowflake (warehouse management, streams/tasks, query optimization).
- Domain Knowledge: Market risk concepts: VaR, SVaR, sensitivities, stress testing. Handling end-of-day market data and historical time series across asset classes.
- Techno-Functional: Ability to translate risk requirements into technical solutions and data contracts.
- Bachelor’s degree, preferably in Computer Science, Engineering, Mathematics, or similar technical discipline.
Personal Attributes:
- Strong analytical and problem-solving skills, including the ability to troubleshoot and resolve complex data related issues.
- Strong verbal and written communication skills.
- Self-starter and entrepreneurial in approach.
- Ability to escalate and follow-up proactively.
- Good time management skills.
Senior Market Risk Developer - Historical Timeseries in London employer: Jefferies
Contact Detail:
Jefferies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Market Risk Developer - Historical Timeseries in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to market risk and data integration. It’s a great way to demonstrate your expertise.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and market risk concepts. Practice common interview questions and be ready to discuss how you’ve tackled data quality issues in the past.
✨Tip Number 4
Don’t forget to apply through our website! We’re always looking for talented individuals who can contribute to our Risk Technology group. Your next big opportunity could be just a click away!
We think you need these skills to ace Senior Market Risk Developer - Historical Timeseries in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Market Risk Developer role. Highlight your experience with Python, SQL, and Snowflake, and don’t forget to mention any relevant market risk knowledge you have. We want to see how your skills match what we’re looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about market risk and how your background makes you a perfect fit for our team. Keep it concise but engaging – we love a good story!
Showcase Your Technical Skills: In your application, be sure to showcase your technical skills clearly. Mention specific projects where you’ve used Python, SQL, or worked with data quality issues. We’re keen to see how you’ve tackled challenges in the past!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at Jefferies
✨Know Your Tech Inside Out
Make sure you brush up on your technical skills, especially in Python and SQL. Be ready to discuss how you've used these tools in past projects, particularly in relation to data sourcing and integration. Familiarise yourself with Snowflake and AWS as well, since they'll be key in your role.
✨Understand Market Risk Concepts
Dive deep into market risk concepts like VaR and SVaR. Be prepared to explain how these concepts apply to the role and share examples of how you've handled end-of-day market data or historical time series in your previous work.
✨Showcase Your Problem-Solving Skills
During the interview, highlight your analytical abilities by discussing specific challenges you've faced in data quality and remediation. Share how you approached these issues and the solutions you implemented, especially any algorithms for gap-filling or anomaly correction.
✨Communicate Effectively
Strong communication is crucial, so practice articulating your thoughts clearly. Be ready to discuss how you've collaborated with teams in the past, particularly with Market Data and Risk stakeholders, to ensure data accuracy and compliance. This will show that you're not just a tech whiz but also a team player.
