Quant Research Analyst

Designation: Quant Research Analyst

Location: Bangalore, Karnataka, India

Responsibilities, aka, what wed like you to deliver:

• Conduct quantitative research to build models related to pricing, promotions, customer

behavior, assortment, demand forecasting, and logistics.

• Apply techniques from statistics, econometrics, machine learning, and optimization to generate actionable insights.
• Work cross-functionally with Product, Engineering, Category, Supply Chain, and Growth teams to identify use cases and translate business problems into analytical models.
• Design and implement A/B tests and experiments to validate hypotheses and measure model performance.
• Present findings and strategic recommendations to stakeholders in a clear, concise, and

actionable manner.

• Collaborate with data engineering and product analytics teams to build scalable,

production-ready solutions.

• Stay up-to-date with advancements in data science, ML, and quantitative methods, and actively contribute to knowledge sharing within the team.

Requirements:

• 1–4 years of experience in a data science, quant research, or analytics role, preferably in

consumer tech, e-commerce, or finance.

• Bachelors/Masters degree in Mathematics, Statistics, Econometrics, Physics, Engineering,

computer Science, Operations Research, or a related field.

• Prior experience building and validating predictive models or optimization algorithms is highly

preferred.

• Strong analytical skills and problem-solving ability; comfort with ambiguity and complex systems.
• Proficiency in Python or R, and strong SQL skills for data extraction and analysis.
• Solid understanding of statistical inference, regression, time-series analysis, and/or machine

learning techniques.

• Experience with tools like Jupyter, Git, and data visualization libraries (e.g., matplotlib, seaborn,

Plotly).

• Ability to communicate complex quantitative results to non-technical audiences effectively.
• Bonus: Experience with forecasting frameworks, optimization libraries (e.g., Gurobi, Pyomo), or

experimentation platforms