Purnartha PMS
Website:
purnartha.com
Job details:
Company Description Purnartha PMS is a SEBI-registered portfolio management firm specializing in research-driven, long-term investment strategies. With over a decade of experience, the company focuses on transparent, client-centric services rooted in the philosophy of “Vasudhaiva Kutumbakam,” treating client portfolios with the same care as their own. Purnartha PMS offers personalized, research-backed Portfolio Management Services aimed at consistent wealth creation and financial growth. The firm emphasizes trust, integrity, and disciplined research in all its investment decisions. Additional regulatory information and office locations are available on the company’s website at www.purnartha.com.
Role Description This is a full-time, on-site Senior Quantitative Analyst role based in Chennai. The Senior Quantitative Analyst will develop, enhance, and validate quantitative models to support portfolio construction, risk assessment, and performance attribution. The role involves analyzing large financial datasets, applying statistical and mathematical techniques to identify patterns, and generating actionable insights for investment decisions. The analyst will collaborate with portfolio managers and research teams to test hypotheses, back-test strategies, and refine risk frameworks. Responsibilities also include preparing clear documentation, creating dashboards or reports for internal stakeholders, and monitoring model performance over time to ensure robustness and regulatory alignment.
Qualifications
- QUANTITATIVE & MARKET RESEARCH Model Development: Design, develop, and backtest quantitative models to identify asymmetric return opportunities. Factor Research: Conduct rigorous factor research across valuation, quality, and momentum, ensuring all models maintain economic interpretability. Risk Analytics: Implement stress testing, Monte Carlo simulations, and predictive risk analytics to ensure portfolio resilience across various market regimes. Performance Attribution: Produce data-backed attribution reports (Sharpe, Sortino, Treynor) and communicate findings to the Investment Committee. EDUCATION AND EXPERIENCE Education: A PhD or Master’s degree in Statistics, Mathematics, Physics, or Financial Engineering. Experience: 5–8 years of professional experience in Data Science or Quantitative Research, with a strict focus on Financial Markets (Asset Management, Wealth Management, or Buy-side Research). Domain Expertise: Strong understanding of Indian equity markets and the fundamental drivers of long-term wealth creation. TECHNICAL SKILLS & COMPETENCIES 1. Advanced Statistical Modeling Systematic Alpha: Proven ability to build models for stock selection and portfolio construction. Predictive Analytics: Deep experience in applying Machine Learning (Random Forest, Gradient Boosting, Deep Learning) to financial datasets while mitigating look-ahead and survivorship biases. Time Series: Mastery of ARIMA, GARCH, and Bayesian inference for market regime detection. Quant Strategy & AI | Purnartha Investment Advisers • • • • • • • • • • • • • • 2. Generative AI & LLM Integration • • • RAG (Retrieval-Augmented Generation): Designing systems that allow the research team to "query" years of annual reports and internal research notes. Investment Synthesis: Leveraging LLMs to automate the extraction of qualitative "moats," management quality indicators, and risk factors. Agentic Workflows: Developing AI agents to automate complex research tasks and cross-reference diverse data streams. Key Performance Indicators (KPIs) • • • Systematization: Successful conversion of manual research processes into data-backed, backtested frameworks. Alpha Generation: Measurable contribution of quantitative signals to identifying high-growth equity opportunities. Efficiency: Reduction in time-to-insight for the research team through the deployment of LLM-based tools.s.
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