Risk Data Analytics Lead

6 days ago

Pune, Maharashtra, India Solytics Partners Full time
About Solytics Partners

We are a leading consulting and solutions provider to the financial services industry, leveraging advanced analytics and technology to deliver accelerated and efficient services and next-generation solutions.

Job Summary

As a Risk Data Analytics Lead, you will play a critical role in driving data-driven decision making within our Risk Management function. You will collaborate closely with senior leadership to understand their needs, develop innovative data visualizations, and provide valuable insights to support risk oversight.

Key Responsibilities
  • Develop effective tools, techniques, metrics, and dashboards to enhance insights and data visualization within the risk management function.
  • Transform business requirements into impactful dashboards, metrics, and visualizations that facilitate risk identification, measurement, and monitoring.
  • Integrate internal and external data to perform analyses that yield valuable insights on risk management strategies and the macroeconomic landscape.
  • Execute quantitative analyses employing statistical methods, econometric techniques, financial modeling, and other risk management practices.
  • Prepare and analyze risk reports for senior management and regulatory authorities.
  • Design, develop, and maintain datasets and pipelines that support risk analytics, focusing on data ingestion, transformation, and quality assurance.
  • Establish and uphold data quality standards and controls to ensure accuracy, consistency, and completeness of data.
  • Utilize industry-leading technologies and incorporate new data attributes to uncover valuable insights and address complex business challenges.
  • Continuously explore innovative technologies and methodologies to enhance our analytics capabilities and provide greater value.
Requirements
  • Over 6 years of experience in the financial services sector, with extensive expertise in risk management, including market risk, credit risk, liquidity risk, and operational risk.
  • Strong quantitative abilities, with proficiency in statistical analysis, econometrics, stress testing, decision science, and various risk measurement techniques.
  • Extensive hands-on experience with key technologies such as Airflow, dbt, Git, Docker, Tableau, Streamlit, AWS, Snowflake, and Python.
  • Advanced SQL skills with a proven ability to design robust data models and optimize query performance.
  • Demonstrated experience in building analytics solutions utilizing Git workflows, modular coding practices, API integrations, and web-based applications.

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