Institutional Shareholder Services
We are currently seeking a Sr. Associate to join our QBIT (Quality Assurance Benchmarking and Independent Testing) Analytics Team in Mumbai, India.
- Independent verification of logical and analytical models used in environmental, social and corporate governance (ESG) risk analysis, investment performance analysis, financial intelligence, stock ranking and portfolio analysis
- Devise data and model verification strategy, develop and implement verification frameworks and prototypes using python/R, and perform data quality analysis
- Closely collaborate with data engineers, software development and product teams to ensure accuracy and reliability of tools and data
- Evaluate model specifications, data processes and business logics for accuracy, completeness, thoroughness and potential dislocations
- End-to-end project and stakeholder management in a global setting
- Software deployment and release management
- Promote an environment that fosters commitment to rigor in data research and analysis operational excellence, collaboration and knowledge sharing
Note: This is a techno-functional role that blends the domains of ESG risk, programming and data analysis. You will primarily work on technologies such as Python/R and MS SQL Server 2017.
- Bachelors/Masters in Engineering/Information Science with strong hands-on experience in analytical programming using Python/R/VBA in the context of data manipulation, transformation, wrangling or analysis
- An MBA (finance), or CFA level 1 or 2, or CIPM will be a big plus
- Overall 6 to 9 years of relevant experience
- Meticulous attention to detail, ability to transform data into actionable insights, identify patterns, trends, relationships and clusters in the data
- Ability to effectively communicate and collaborate with global business and technical teams
- Self-starter and quick-learner
- Ability to adapt and work in a fast-paced environment independently with little supervision
Please Note : The job role does not involve work related to Machine Learning.