Pratik D. Kale
About Blogs

Pratik D. Kale

Quantitative Researcher focused on execution, signal engineering, and financial modeling. Building robust research pipelines and finance-grade systems.

Download Resume
Worked with: Fidelity Investments • Tata Consultancy Services (TCS) • KPMG
Profile photo

Major Work

Solving user and business problems with data-driven finance and scalable systems.

FinTech

Dynamic Yield Curve Modeling & Macro Signals

Modeled the U.S. Treasury yield curve with the Dynamic Nelson–Siegel state-space model and Kalman filtering, then forecasted 2s10s using the slope factor. Built thresholded trading signals and evaluated PnL behaviour.

View Project →
project_image_2
Execution

Optimal Trade Execution via RL

Gym-compatible execution environment on SPY 1-minute data with market impact. PPO agent reduced implementation shortfall and outperformed TWAP/VWAP baselines on multiple test windows.

View Project →
Options

Delta–Gamma Hedging Strategy

Simulated and compared a Long Straddle and a Delta–Gamma hedged portfolio using SPY option chains. Visualized convexity, sensitivity, and relative risk across regimes.

View Project →

Hold on, you will see more in the PROJECTS section below.

Experience

Quantitative Research Assistant - Stevens Institute of Technology

Hoboken, NJ • May 2025 - Aug 2025
  • Replicated four asset allocation strategies from DeMiguel et al. (Equal-Weight, Mean-Variance, Minimum-Variance, Value-Weighted) using real market cap and returns data.
  • Cleaned and merged multi-source datasets (Fama-French factors, 25-portfolio returns, market caps), aligning timeframes and reducing to 20 usable portfolios.
  • Computed Sharpe Ratios, Certainty-Equivalent Returns, and p-values using 60-month rolling windows to compare in-sample and out-of-sample performance.
  • Designed a reinforcement learning-based trading agent (85%+ signal accuracy) and evaluated 1000+ simulations to analyze execution cost, turnover, and robustness.

Cloud Engineer (Asset Management) — Fidelity Investments

Bangalore, IN • Dec 2021 - Jan 2025
  • Delivered blockchain-enabled financial infrastructure by tokenizing retail investment transactions using Ethereum-compatible networks (Polygon, ERC-20), enabling secure, on-chain representation of over $250M in client assets across fixed income and equity segments.
  • Designed and implemented 2 custom Groovy libraries supporting fully automated CI/CD pipelines for Node and Java-based fintech applications and Ethereum smart contracts; improved deployment efficiency by 60%, accelerating time-to-market for investment tools.
  • Developed a quantitative platform enabling ML-driven portfolio optimization, Sharpe ratio enhancement, and factor-based alpha signal generation for Strategic Investments; integrated time-series models and supported live execution strategies; integrated boto3 for automation, resulting in 80% reduction in manual tasks and faster alpha generation from models.
  • Represented the firm as a Quantitative Analytics SME at Fidvantage 2023, showcasing advancements in financial data engineering, accounting for 40% of tech innovation coverage across data warehousing, trade analytics, and factor modeling.
  • Built a custom Python library atop Spring Boot services to support cloud-native deployment of ML models used in asset pricing, risk forecasting, and back testing strategies; reduced spin-up time by 70% and ensured 95% CI/CD reliability.
  • Spearheaded Cloud FinOps cost-optimization for real-time financial data pipelines used in risk reporting and trade reconciliation; achieved $1.4M+ in annualized cost savings, aligning with compliance and operational efficiency KPIs.

Full Stack Engineer — Tata Consultancy Services

Bangalore, IN • Nov 2020 - Nov 2021
  • Served as Python Backend Developer for client Morrisons UK PLC, building AWS serverless microservices for order estimation and inventory automation, enhancing the order processing speed by 42% and reducing inventory reporting latency by 35%.
  • Devised and developed REST APIs using Flask REST Framework.
  • Leveraged AWS Services (Lambda, ECS, S3, SNS, Eventbridge, CloudWatch, RDS) and Terraform for project deliverables, completing 5+ production releases with zero critical errors and 100% SLA adherence.

Data Analyst Intern — KPMG

Virtual • Apr 2020 - Jun 2020
  • Performed feature engineering, data wrangling, data analysis, and data visualization to support business insights during the internship.
  • Conducted end-to-end analysis of large datasets for a multinational cycling company using Excel, SQL, and Python.
  • Developed interactive Tableau dashboards to automate weekly KPI reporting, improving stakeholder visibility and reporting speed by 30%.
  • Applied statistical data analysis techniques with Python and Pandas to identify trends, patterns, and actionable recommendations.

Research Assistant — College of Engineering Pune

Pune, IN • Jun 2018 - Jul 2018
  • Assisted a lead researcher in developing video-based anomaly detection procedures, undertaking experimentation and technical reporting for a real-time monitoring system.
  • Studied anomaly detection and implemented the License Plate Number Detection System using OpenCV (Computer Vision) and Machine Learning.
  • Worked with Python programming language, applying the KNN Algorithm on EMNIST MNIST Dataset.

Research Intern — National Informatics Centre

New Delhi, IN • Jun 2017 - Aug 2017
  • Assisted senior analysts in economic and policy data analysis on government defense projects and contributed to composing sections of national development reports.
  • Collaborated with NIC officials to develop a website for automating acceptance of school applications for government-funded incubation programs under the Atal Tinkering Labs initiative.
  • Supported a joint initiative of Government of India & Atal Innovative Mission (AIM) to streamline application processes for incubation programs.

Academics

Stevens Institute of Technology
Graduate GPA 3.84

MS, Financial Technology & Analytics

Stevens Institute of Technology • Jan 2025 – Dec 2026

  • Applied Statistics in Finance
  • Probability Theory
  • Financial Technology
  • Big Data Technology
  • Financial Risk Management
  • Financial Data Science
  • Intro to Bloomberg & Refinitiv
SGB Amravati University
Undergraduate CGPA 8.74

BE, Information Technology

SGB Amravati University • Aug 2016 – May 2020

  • Database Management Systems
  • Artificial Intelligence
  • Web Technology
  • Computer Architecture
  • Operating Systems
  • Web Commerce

Projects

Dynamic Nelson–Siegel factors
MacroTime‑Series

Dynamic Nelson–Siegel & Macro Signals

Kalman‑filtered β₀/β₁/β₂, 2s10s forecasting from β₁, signal thresholds, and backtests.

  • State‑space modeling & forecasting
  • Thresholded trading signals
GitHub
RL Execution
ExecutionRL

Optimal Trade Execution via Reinforcement Learning

Custom Gym environment on SPY 1‑minute data; PPO agent reduced implementation shortfall vs TWAP/VWAP.

  • Market impact & slippage modeling
  • PPO training and evaluation
GitHub
Delta Gamma Hedging
OptionsGreeks

Delta–Gamma Hedging Strategy

Compared Long Straddle vs Delta‑Gamma hedged portfolio using SPY option chains; convexity visualization.

  • Black‑Scholes Greeks estimation
  • Regime sensitivity analysis
GitHub
Rare event detection
AnalyticsAnomaly

Rare Events in Low‑Frequency Data

Isolation Forest / LOF with sentiment overlays; custom hyperplane classifier for liquidity anomalies.

  • 92% precision on low‑liquidity anomalies
  • Interactive R Shiny dashboard
GitHub
Stock prediction from Twitter sentiment
NLPTime‑Series

Single Stock Price Prediction using Twitter

Engineered an NLP‑driven sentiment + time‑series pipeline to predict directional moves using ARIMA/XGBoost; integrated Yahoo Finance and Twitter APIs for real‑time signals and backtests.

  • Technologies: Python, Pandas, scikit‑learn, XGBoost, ARIMA
  • Sentiment extraction and feature engineering from tweets
  • 86% directional accuracy on holdout period
GitHub
License Plate Recognition System
Computer VisionIoT

License Plate Recognition System

Spearheaded a number‑plate detection and recognition system using KNN (Contour method); detects suspected vehicles, reads the plate, and stores the record for future use.

  • Technologies: Python, OpenCV, scikit‑learn, Raspberry Pi
  • Contour‑based localization and KNN OCR workflow
  • Edge capture + centralized storage pipeline
GitHub
Moody Player project
SpeechNLP

Moody Player — Voice‑Based Mood Detection & Music Player

Interactive desktop assistant that chats briefly, infers mood via sentiment analysis, and plays a relevant playlist from YouTube with a lightweight GUI.

  • Technologies: Python, speech‑recognition, TextBlob/VADER, Tkinter
  • Randomized daily questions to avoid repetition
  • JSON‑driven playlists and prompts
GitHub
Hospital Management System
DesktopSQLite

Hospital Management System (HMS)

Desktop application to streamline patient care, scheduling, and record‑keeping with modules for patients, doctors, appointments, and medical records.

  • Technologies: Python 3.x, Tkinter, SQLite3
  • Search & filter across patient/doctor records
  • Clean, lightweight GUI for quick actions
GitHub

Certifications

AWS Solutions Architect Associate (SAA‑C03)

Amazon Web Services • 2023

View Credential

Publications

IJITEE paper cover
Journal IJITEE 2020

Big Data for Surveillance in Mobility Sector: Applications and Opportunities

International Journal of Innovative Technology and Exploring Engineering, 2020

  • Keywords: Transport, Mobility, Big Data, IoT, Surveillance, Computer Vision.
  • Scope of the Article: IoT
View Paper

Awards and Recognitions

Awards

  • 2018 – 1st Rank — All India Innovative Idea Pitching Competition, NIT Nagpur, IN
  • 2017 – 1st Rank — Project Competition, Engineering India Foundation, Nagpur
  • 2018 & 2019 – 1st Runner‑up — Division Level Quiz Competition, Maharashtra, IN
  • 2017 & 2018 – 1st Runner‑up — Mock Placement Competition, MCOET Shegaon
  • 2019 – Top 10/500 — Smart Industry Hackathon, Tata Consultancy Services (Nagpur, IN)
  • 2021 – Top 50 — TCS Kickoff Hackathon

Recognitions

  • 2024 — Fidelity Eureka Award (Fidelity Investments) for achievement in Financial Operations by optimizing workflow.
  • 2022 — Recognized by Customer/Consumer for “Customer Obsessed” behavior (Fidelity Investments).
  • 2019 — Special Achievement Award from Sipna College of Engineering for inter‑university representation.
  • 2019 & 2020 — Co‑Convener and Convener of the National Level Technical Festival “VIDYOTAN”.

Testimonials

“

Highly motivated and quick learner with a strong proficiency in Python and AWS. Committed to staying at the forefront of technology trends, ensuring efficient and effective solutions. Experienced troubleshooter with a strong sense of independence. Proven track record of resolving issues and ensuring smooth operations. Ready to take on new responsibilities and add value to any team.

Priya Shah
Priya Shah
Principal Engineer, Fidelity Investments (AI/ML Platform Lead)
LinkedIn
“

Pratik is an exceptional Python developer. His knowledge of Python and AWS services is what I personally have seen and appreciate during his tenure in the project. He has extremely good organizational and analytical capabilities and is able to work well on a team . Pratik would be an asset for any organization.