Senior Associate/Senior Quantitative Fund Modeler - Private Markets - Banking/Financial Services

Role Overview:

We are seeking a highly analytical Quantitative Fund Modeler to join our Mumbai-based global Portfolio Management team. This is a hands-on, model-building role focused on developing sophisticated frameworks for fund forecasting, portfolio construction, and investment decision-making within private markets.

Key Responsibilities:

- Design, build, and maintain end-to-end quantitative models for fund-level and portfolio-level analysis.

- Develop frameworks for cash-flow projections, NAV evolution, scenario analysis, and investment outcome forecasting.

- Apply advanced techniques including Monte Carlo simulations, stochastic modeling, and probabilistic methodologies.

- Translate complex quantitative outputs into actionable investment insights for global stakeholders.

- Document model methodologies, assumptions, and limitations while ensuring robust validation and continuous enhancement.

- Collaborate with investment teams to automate and scale portfolio-modeling capabilities.

Required Skills & Experience:

- Proven experience in quantitative research, financial modeling, or data science within the financial services sector.

- Strong proficiency in Python and experience working with large, complex financial datasets.

- Deep expertise in building models from scratch using simulation-based and probabilistic techniques.

- Solid foundation in statistics, mathematics, and numerical analysis.

- Strong communication skills with the ability to explain technical methodologies to non-quantitative stakeholders.

- Demonstrated ability to take full ownership of the model development lifecycle.

Nice to Have:

- Prior exposure to private markets, including private equity, private credit, or infrastructure.

- Familiarity with Takahashi-Alexander-style fund modeling or similar cash-flow forecasting methodologies.

- Relevant postgraduate degrees or professional certifications.

Education:

A strong academic background in a quantitative discipline is required, such as Mathematics, Statistics, Financial Engineering, Quantitative Finance, Economics, Econometrics, Computer Science, Engineering, Data Science, or Finance.