Job Responsibilities
- Develop and enhance a robust analytics framework and infrastructure for ADTV time series data for financial instruments across multiple asset classes
- Research and develop next-generation outlier and variance detection methodologies
- Build outlier detection and missing data imputation tools, employing statistical tests and analyze their performance
- Industrialize and automate the Average Daily Trading Volume production process
- Design and develop a scalable framework that can easily onboard new data source while adapting to evolving analytics needs
- Create, maintain and enhance APIs and statistical tools used for time series data management and visualization
- Develop and implement front-end analytics and applications to deliver end-to-end market data solutions
- Review code changes of team members and provide framework related guidance
- Lead project and working group meetings with well-defined agenda and drive project deliveries with multiple stakeholders
- Liaise and collaborate with various functions including peer Market Risk Coverage, Credit Risk and Technology partners
- Facilitate periodic audit processes to ensure compliance with regulatory bodies
Required qualifications, capabilities, and skills
- Bachelor's degree in a quantitative field
- 5+ years of expertise in Python, knowledge of object-oriented programming (OOP) and experience with Numpy and Pandas
- Experience in end-to-end delivery of cross functional projects
- Ability to perform code optimization, debugging and reverse engineering
- Experience in analyzing large and unstructured datasets
- Knowledge of financial instruments and risk management principles
- Strong analytical skills with a keen attention to detail
- Ability to independently problem solve and take ownership for delivery
- Ability to think critically and adapt to rapidly changing requirements
- Excellent verbal/written communication skills and proficiency in technical documentation
- Enthusiasm for knowledge sharing and ability to collaborate effectively
Preferred qualifications, capabilities, and skills
- Advanced degree in Financial Engineering, Computer Science, or related quantitative field
- Knowledge of front-end technologies like React, JS, HTML and integration with large data sets
- Proficient in Microsoft Excel, using advanced formulas, pivot tables, etc.
- Strategic and creative thinker when faced with problems and opportunities
- Ability to understand business processes and their risk implications, analyze complex situations, reach appropriate conclusions and make feasible recommendations
- Chartered Financial Analyst or Financial Risk Manager qualifications preferred