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Senior Quantitative Risk Specialist in Bengaluru

3 weeks ago


Bengaluru, Karnataka, India beBeeRiskAnalysis Full time

Key Responsibilities

Risk Analyst - Software Engineering in Bengaluru will be responsible for delivering critical regulatory and risk metrics analytics across risk domains (market, credit, liquidity, operational, capital) and firm activities via regular reporting, customized risk analysis, systematically generated risk reporting and risk tools.

This role has a unique vantage point in the firm s risk data flows that, when coupled with a deep understanding of client and market activities, allows it to build scalable workflows, processes and procedures to deliver actionable risk insights.

The following are core responsibilities for this role:

  • Delivering regular and reliable risk metrics, analytics insights based on deep understanding of the firm s businesses and its client activities.
  • Building robust, systematic efficient workflows, processes and procedures around the production of risk analytics for financial non-financial risk, risk capital and regulatory reporting.
  • Attesting to the quality, timeliness and completeness of the underlying data used to produce these analytics.

Candidates Requirements

Eligible candidates are preferred to have the following:

  • Masters or Bachelors degree in a quantitative discipline such as mathematics, physics, econometrics, computer science or engineering.
  • Entrepreneurial, analytically creative, self-motivated and team-oriented.
  • Excellent written, verbal and team-oriented communication skills.
  • Experience with programming for extract transform load (ETL) operations and data analysis (including performance optimization) using languages such as Python, Java, C++, SQL and R.
  • Experience in developing data visualization and business intelligence solutions using tools such as Tableau, Alteryx, PowerBI, and front-end technologies and languages.
  • Working knowledge of the financial industry, markets and products and associated non-financial risk.
  • Working knowledge of mathematics including statistics, time series analysis and numerical algorithms.
  • 3+ years of financial or non-financial risk industry experience.