Python in Finance Training Quant Models

Job Description

PyStatiQ by PredictRAM Quantitative Finance Internship Opportunity For Aspiring FinTech Coders | ₹5,000 Top Performer Prize Location: Remote (Online) Duration: 3 Weeks Stipend: Top performers earn ₹5,000 + industry recognition + Cetrificate Responsibilities As a Quantitative Finance Intern, you will: Develop Python-based financial models for CAPM and Beta calculations Implement regression analysis on real market data (NSE stocks) Create data visualization dashboards for risk assessment Optimize code for computational efficiency Document financial methodologies and code logic Present findings to industry mentors Participate in weekly code review sessions Complete assigned quantitative finance projects Qualifications Required: Pursuing/completed Bachelor's in Finance, Economics, CS, or related field Python programming fundamentals (variables, loops, functions) Basic understanding of financial concepts (stocks, indices, returns) Ability to work with APIs and financial datasets Strong analytical and problem-solving skills Preferred: Experience with pandas, NumPy, or matplotlib Knowledge of statistical concepts (regression, correlation) Previous coursework in quantitative finance Familiarity with yfinance or similar financial data libraries GitHub portfolio demonstrating coding projects About the Internship You'll gain hands-on experience in: Implementing CAPM models and beta calculations Analyzing real stock data (TCS, ITC, WIPRO vs. NIFTY 50) Developing financial risk assessment tools Working with our browser-based Python IDE Receiving mentorship from SEBI-registered experts Current Challenge: "Build a Beta Calculator using yfinance data" Why Join? Prove Your Skills: Top performers receive ₹5,000 stipend Industry Exposure: Code reviewed by quant finance veterans Career Gateway: Interviews with partner firms for top candidates Skill Certification: Earn PyStatiQ Quantitative Finance Certificate Cloud IDE Access: Browser-based coding environment with datasets Show more Show less