EOS RPO
Quantitative Researcher / Data Scientist
Experience from 3 to 9 years
Quantitative Research & Portfolio Data Analyst
Location: Pune, India
About the FirmAs a leading global investment management firm, our organization fosters diverse perspectives and embraces innovation to help clients navigate the uncertainty of capital markets. Through high-quality research and diversified investment services, we serve institutions, individual investors, and private wealth clients across major markets worldwide. Our ambition is simple: to be our clients’ most valued asset-management partner.
With thousands of professionals spread across major international financial hubs, our people are our distinct advantage. We foster a culture of intellectual curiosity and collaboration to create an environment where everyone can thrive and do their best work. Whether producing thought-provoking research, identifying compelling investment opportunities, infusing new technologies into our operations, or providing thoughtful advice, we look for unique voices to help lead us forward.
Role OverviewWe are seeking a high-caliber Quantitative Research & Portfolio Data Analyst to join our team in Pune. In this role, you will play a critical part in supporting global asset allocation, data engineering, statistical modeling, and bespoke portfolio analysis for premier institutional and private wealth clients.
Key Day-to-Day Responsibilities:
Quantitative & Portfolio Research: Conduct asset allocation and manager evaluation research; perform bespoke client portfolio analysis and construct custom portfolio models for internal and external stakeholders.
Data Engineering & Analytics: Handle end-to-end data collation, cleansing, and manipulation (SQL, Python); respond to bespoke data analysis requests across complex financial datasets.
Database & Infrastructure Development: Design and build new databases using multi-source data feeds, establishing scalable infrastructure for ongoing maintenance.
Data Visualization & Automation: Build interactive dashboards (Python Dash) and produce automated analytical reports using custom Python pipelines.
Statistical Modeling & Machine Learning: Apply statistical techniques and machine learning models to solve complex quantitative problems in fundamental and systematic strategies.
AI Tool Integration: Leverage modern AI tools to optimize data handling, quantitative research, and predictive modeling workflows.
Essential / Must-Haves:
RDBMS & Database Architecture: 2+ years of hands-on experience in relational database design, with a strong preference for MS SQL Server.
Advanced Python Development: 2+ years of core Python experience, with proven mastery in data manipulation and statistical libraries (Pandas, NumPy, Statsmodels are mandatory).
Big Data Handling: Demonstrated capability in cleaning, processing, and manipulating large-scale quantitative datasets with exceptional accuracy.
Attention to Detail: High level of precision, rigor, and commitment to data integrity.
Desirable / Good-to-Haves:
Quantitative Modeling: Experience building quantitative models, factor research, portfolio construction techniques, or systematic trading/investment frameworks.
Python Ecosystem: Familiarity with specialized libraries such as Dash, PyPfOpt, CVXPY, Keras, or Scikit-Learn.
Domain Knowledge: Understanding of financial statements, corporate accounting principles, and portfolio risk analysis.
AI Readiness: Hands-on experience or familiarity with leveraging AI-driven workflows in research and modeling.
Academic & Soft Skills:
Education: Bachelor’s or Master’s degree in Mathematics, Physics, Statistics, Econometrics, Computer Science, Engineering, or a related quantitative field.
Communication: Excellent verbal and written English communication skills, with a proven ability to collaborate effectively with global cross-functional teams and stakeholders.
Brand Neutralization: Replaced direct mentions of "AB" and specific firm counts with generalized, top-tier industry phrasing ("our organization", "leading global investment management firm", "thousands of professionals spread across major international financial hubs").
Location Updated: Explicitly set to Pune, India.
Clarity & Structure: Grouped requirements cleanly into clear categories (Must-Haves, Good-to-Haves, Academics) for faster scanning by potential candidates.