Omkar Mahale FinTech • Product • Quant Research
Master of Science in Financial technology & analytics • Stevens Institute of Technology • GPA 3.8 / 4

I build finance products and quant frameworks that work in the real world.

Product manager & Founder at SIPly (an AI-driven Ed-Fintech platform) and Research Assistant, analysing high-frequency data (HFD) to detect rare liquidity events and generate algorithmic trading signals.

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Email 099omkarmahale@gmail.com Phone 201-238-6377 LinkedIn /in/omkar-mahale-rr99

Experience

High-signal roles, written for fast recruiter scanning.

SIPly Inc — Product manager & Founder

New Jersey, USA • Jan 2025 – Present
Product
  • Architected SIPly’s fintech revenue and pricing engine by designing SIP-based micro-savings mechanics, credit-partner yield-sharing structures, and automated escrow-style fund flows, ensuring capital protection logic, regulatory-aware fund segregation, and sustainable cash-flow modelling.
  • Developed data-driven unit economics and growth models using cohort retention analysis, funnel conversion tracking, LTV/CAC scenario simulations, and pricing sensitivity testing to validate scalability and long-term revenue sustainability.
  • Led beta launch execution and rapid user acquisition strategy, onboarding 120 users within 24 hours, and built early-stage analytics dashboards to evaluate activation rates, behavioural flows, and conversion signals to assess initial product–market fit.
  • Directing day-to-day startup operations and cross-functional coordination in a bootstrapped environment.

Stevens Institute of Technology — Research Assistant

Hoboken, NJ • June 2025 – Present
Research
  • Conducted quantitative financial research on S&P 500 stocks, commodities, and ETFs, analysing liquidity, market efficiency, and price behaviour using OHLCV, Level-2, order book, and COT data.
  • Built statistical and machine-learning-based trading frameworks to reconstruct order books and identify rare liquidity events.
  • Backtested trading strategies across multiple market regimes, evaluating performance, drawdowns, and execution.

Vtask Investments — Quantitative Analyst

India • Jun 2023 – Dec 2024
Trading
  • Evaluated multi-asset trades across equities, FX, & commodities using model-driven signals, performing pre-trade validation, risk checks, and execution feasibility analysis to ensure alignment between quantitative outputs and live market conditions.
  • Applied quantitative and market microstructure analysis to assess price behaviour, liquidity conditions, volatility regimes, and order flow dynamics, supporting structured trade selection and timing decisions.
  • Translated complex financial data into actionable insights by combining fundamental inputs, statistical indicators, and pricing models, producing step-by-step analytical reasoning for internal strategy reviews and client-facing discussions.
  • Developed performance attribution and risk analytics reports, breaking down P&L drivers, drawdowns, exposure concentration.

Graduate Academic Tutor — Stevens Institute of Technology

August 2025 – Present
Leadership
  • Assisting the professor in guiding students with credits like statistical learning, financial data science, and quantitative modelling & financial lab.

Academic Projects

Two focused highlights (no clutter).

Multi-Asset Portfolio Optimisation

Fall 2025 • Interactive Brokers • $100,000 initial capital
Portfolio
  • Working on a portfolio construction project using Interactive Brokers simulation with an initial capital of $100,000, actively managing investments over the last two quarters of 2025.
  • Applying Fundamental & Macroeconomic Analysis, machine learning models, and advanced risk management techniques, Liquidity & Flow Analysis to optimise portfolio performance.
  • The portfolio was diversified across ETFs, S&P 500 and NASDAQ equities, and commodities.

Predictive Analytics for Consumer Loan Risk Management

Spring 2025 • 1M+ LendingClub loan records
ML
  • Worked on ML models to predict early loan defaults and returns, leveraging 1 million+ LendingClub loan records enriched with 94 firm-specific features and 8 macroeconomic indicators.
  • Optimised models using LLMs and agentic integration, enabling scalable analysis of complex, high-volume datasets and improving predictive accuracy on default risk.

Skills

Grouped to stay simple and readable.

Programming

R Python SQL C++

Software

Bloomberg RStudio Cursor AI PgAdmin4 N8N Alteryx Airtable MS Office

Certifications

  • Bloomberg, 2025 | Bloomberg Finance Fundamentals
  • National Association of State Boards of Accountancy (NASBA), 2025 | Financial Foundations

Education

Degree details (from resume).

Stevens Institute of Technology, Hoboken, NJ

Expected December 2026
MS
  • Master of Science in Financial technology & analytics | GPA: 3.8 / 4
  • Relevant Coursework: Financial Data Science, Statistical Learning, Probability Theory, Risk Management, Investment Management, ML in Finance, Financial Technology, Blockchain & Defi Finance

Terna Engineering, Mumbai University, Navi Mumbai, Maharashtra, India

2021–2024
BE
  • BE in Mechatronics | GPA: 3.6 / 4
  • Relevant Coursework: Machine interface design, Python programming lab, Industrial economics, Neural network & Fuzzy Logic

Contact

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