Responsibilities:
- Independent verification of logical and analytical models used in environmental, social, corporate governance (ESG) risk analysis, investment performance analysis, financial intelligence, stock ranking, portfolio analysis, and market intelligence.
- 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 the accuracy and reliability of tools and data
- Evaluate model specifications, data processes, and business logic 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 a commitment to rigor in data research and analysis operational excellence, collaboration, and knowledge sharing
- To start with, this will be an individual contributor role but in future there will be opportunities to lead a team.
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.
Qualifications:
- Bachelors/Masters inEngineering/InformationScience with strong hands-on experience in analytical programming using Python/R in the context of data manipulation, transformation, wrangling, or analysis
- An MBA (finance), 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.
