Job Purpose: This role is a cross-asset data scientist role with specialization in stress loss / credit capital computations working as part of Markets Capital Advancement team, to help Markets more actively manage capital and TCE (Tangible Capital Equity). You will be responsible for analyzing, presenting and sharing stress loss / capital and related data.
Job Background/context: Within Counterparty Trading & Risk, the Markets Capital Advancement team is the central team that drives and oversees execution and management of capital initiatives. The XVA trading desk (part of Counterparty Trading and Risk) is responsible for the pricing and subsequent risk management of derivatives trades including the use of credit, funding and capital. The In-Business Market Risk team is responsible for market risk across asset classes. As part of both teams’ mandate to facilitate business and manage return on capital, the desks need Front Office staff focused specifically on capital for Markets.
Key Responsibilities:
- Build tools and frameworks for data analytics allowing for better understanding of stress loss data across asset classes
- Develop frameworks to identify key drivers of impact of stress loss on TCE and regulatory submissions
- Identify and work on resolving issues such as data quality, methodology errors, implementation errors, enhancing data coverage, etc.
- Build and host dashboards & performance visualizations on capital and connected datasets, with strong emphasis on turning insights into actions
- Partner with capital management, traders, finance, reporting, program execution and tech teams on various initiatives
- Develop in-depth knowledge and proficiency of supported business areas and engage business partners in evaluating opportunities for process integration and refinement
- Maintain and enhance the github repository
Knowledge/Experience:
- Experience with wholesale and counterparty risk capital calculation methodologies
- Experience working with data analytics on large datasets
- Proven ability analyzing business needs, building visualizations, and tracking down complex data quality and integration issues
- Understanding of balance sheets and regulatory capital requirements would be an added advantage
- 6-10 years experience in financial industry using tools for statistical modeling of large data sets
Skills:
- Very strong SQL and Python skills required
- Previous experience with streamlit will be an advantage
- Strong analytical and mathematical skills.
- Attention to detail.
- Demonstrable team skills both within and across teams.
- Ability to pick up new concepts and think outside the box.
- Preferably comfortable with derivatives modelling concepts.
Education:
- Bachelor’s/University degree or equivalent experience, potentially Masters degree
What Citi Can Offer You
By joining Citi London, you will not only be part of a business casual workplace with a hybrid working model (up to 2 days working at home per week), but also receive a competitive base salary (which is annually reviewed), and enjoy a whole host of additional benefits such as:
- 27 days annual leave (plus bank holidays)
- A discretional annual performance related bonus
- Private Medical Care & Life Insurance
- Employee Assistance Program
- Pension Plan
- Paid Parental Leave
- Special discounts for employees, family, and friends
- Access to an array of learning and development resources
Alongside these benefits Citi is committed to ensuring our workplace is where everyone feels comfortable coming to work as their whole self, every day.
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Job Family Group: Technology------------------------------------------------------
Job Family:Data Science------------------------------------------------------
Time Type:Full time------------------------------------------------------
Most Relevant Skills Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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