Note: The job is a remote job and is open to candidates in USA. Indiggo is an innovative fintech company that measures and ranks companies using a proprietary corporate leadership model and AI-driven platform. The Director, Research Operations and Analytics will manage the end-to-end data, AI, metrics, and ranking pipeline while coordinating data science, software engineering, and research teams. The role will oversee quality assurance, index analytics, model translation, quantitative research, and workflow automation.
Responsibilities
- Research Management: Substantially own and manage the operational lifecycle of our data/AI/metric/ranking pipeline, ensuring production timelines, process fidelity, and delivery milestones are consistently met
- Cross-Functional Alignment & Project Management: Coordinate directly between data scientists, software developers, and research experts to ensure clear workflow priorities, crisp documentation, and alignment on core deliverables
- Pipeline Integrity & QA Governance: Oversee the continuous flow of data ingestion, validation, and output accuracy, establishing rigorous quality-control benchmarks across every layer of scoring and ranking
- Index Performance & Product Analytics: Support the analytical evaluation, back testing, and performance attribution of existing indexes and new investment product strategies
- Model Translation: Partner closely with data science and software engineering teams to translate mathematical and statistical models into functional production code, specifications, and architecture
- Quantitative Insights & Trend Research: Conduct targeted quantitative research projects to uncover emerging leadership trends and actionable insights from our collected metrics
- Workflow Optimization & Scripting: Utilize Python and Excel to build automated QA scripts, streamline data operations, and continuously refine production workflows
Skills
- Proven ability to manage complex research workflows, coordinate cross-functional technical teams, and drive operational clarity without heavy existing structure
- Expert-level Excel skills (advanced formulas, complex financial/data modeling, and sheet auditing)
- Strong coding capabilities in Python for data manipulation, scripting, quantitative modeling, and QA automation (e.g., Pandas, NumPy)
- Deep understanding of quantitative analytics, statistical modeling, indexing methodologies, financial markets, and corporate evaluation metrics
- Demonstrated experience translating complex mathematical and statistical models into clear technical specifications and production-ready code in collaboration with software engineering teams
- Exceptional communication skills to articulate complex data issues, facilitate cross-team problem-solving, and report directly to the Chief Research Officer
- High sense of accountability and a rigorous mindset for auditing data quality prior to production deployment
- 6-8+ years of experience in quantitative research, data operations, or research management roles within fintech, asset management, or data-intensive investment firms
- Bachelor's or Master's degree in Finance, Economics, Quantitative Finance, Data Science, Mathematics, or a related field
Benefits
- Directly report to the Chief Research Officer and own the operational aspects of a cutting-edge fintech platform.
- Work at the intersection of corporate leadership, quantitative research, AI, and financial product development (ETFs and indexing).
- Enjoy high autonomy, leadership exposure, and the opportunity to shape both process operations and research strategy.
Company Overview