Hi, I'm Arnav Jain
Data & Machine Learning Enthusiast
Solving problems, decoding data, optimizing solutions, driving impact.
About Me
Passionate about transforming data into intelligence.
Data Enthusiast
Transforming raw data into meaningful insights that drive decision-making.
Problem Solver
Tackling complex challenges with innovative solutions and analytical thinking.
Tech Innovator
Exploring cutting-edge technologies to push the boundaries of data science.
I'm a problem solver at heart, always drawn to challenges that require strategy, logic, and creativity. Whether it's building machine learning models, optimizing systems, or uncovering insights from complex data, I thrive on finding smart, efficient solutions.
Beyond work, I love strategy and competition—whether it's playing chess and poker, analyzing soccer tactics, or diving into the precision of Formula 1. I enjoy the mental agility these games and sports demand, much like solving real-world problems.
Projects
Some of the projects I have worked on
Portfolio Optimization using Machine Learning
Developed an advanced portfolio optimization system leveraging machine learning techniques, specifically Agglomerative Clustering. The project identifies stocks with similar risk and return metrics, clustering them to create diversified and efficient portfolios.
AI Trading Agent
Developed a trading agent using Reinforcement Learning to adapt to market conditions dynamically. Outperformed the Buy-and-Hold strategy by 15% in cumulative returns on backtesting with S&P 500 data.
Depressive Disorder Prediction
Developed a Machine Learning model using BRFSS 2021 dataset to predict depressive disorders. Achieved 75% TPR for both classes through extensive data analysis.
Skills
The tools and technologies I excel in:
Programming Languages
Data Analytics & BI
Machine Learning & Deep Learning
Big Data & Cloud Computing
Software Development
Data Visualization
Education
My academic journey and qualifications
Master of Science in Applied Data Analytics
Boston University
Boston, MA | September 2023 - January 2025
- GPA: 3.8/4.0
- Relevant coursework: Data Visualization, Data Mining, Web Mining, Deep Learning, Machine Learning, Financial Analysis, Statistical Analysis, Data Structures, Algorithm Performance Analysis, Computational Mathematics, Data Analysis
Bachelor of Technology in Computer Science
Manipal University Jaipur
Jaipur, India | August 2019 - July 2023
- GPA: 8.21/10 (3.53 on 4-Point Scale)
- Relevant coursework: Financial Mathematics, Machine Learning, Deep Learning, Macroeconomics, Cloud Computing, Database Management, Data Manipulation, Data Extraction, Data Transformation, Spatial Data Analysis, Statistics
Certifications
Professional certifications and achievements
Neural Networks and Deep Learning
DeepLearning.AI
January 2022
Comprehensive course covering supervised learning, unsupervised learning, and deep learning techniques.
Generative AI: Introduction and Applications
IBM
January 2025
Detailed course, covering the complex topic of Generative AI, and it applications.
Python for Data Science, AI & Development
IBM
January 2025
Certification showcasing proficiency in Python for Data Science and Machine Learning development.
Work Experience
Data Analytics & Machine Learning Fellow
Elevate Me
Columbus, Ohio | January 2025 - Present
- Engaging in 150+ hours of hands-on learning and project work, including active participation in a live project and two optional capstone projects.
- Apply data analytics and machine learning techniques to address real-world problems.
- Utilize advanced tools such as Python, Jupyter Notebooks, Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn to build and evaluate machine learning models
- Deploy machine learning models on Microsoft Azure, integrating Azure ML with Azure SQL databases to enable real-time analytics and predictions
- Perform data preprocessing, feature engineering, and model selection, and evaluate regression, classification, and clustering algorithms to optimize performance
- Collaborate in a professional team environment using tools like Jira, Confluence, and Slack for project management and effective communication.
Tools: Azure, Jira, Confluence, Slack, Jupyter Notebook, Python, SQL, R
Data Analyst Intern
Omalco Extrusions
New Delhi, India | June 2022 – July 2023
- Developed and deployed real-time interactive dashboards using Power BI, DAX, and SQL, optimizing operational monitoring and decision-making, leading to a 10% increase in efficiency.
- Conducted exploratory data analysis (EDA) and applied predictive modeling techniques, including linear regression and hypothesis testing using R and Python, to uncover key business trends and optimize strategic planning.
- Automated data pipelines and ETL workflows using SQL and Python, enhancing data integrity, accessibility, and processing speed, reducing manual reporting efforts by 50%.
- Transformed complex analytical findings into executive-level insights, presenting data-driven recommendations through visually compelling reports and dashboards, driving strategic decision-making across departments.
Tools: Power BI, Tableau, Streamlit, R-Studio, R, Python, SQL, Azure
Proprietary Trader
Jain Capital
Jaipur, India | May 2020 – March 2022
- Developed and deployed algorithmic trading models using Python and PineScript, integrating multi-factor fundamental analysis, technical indicators, and machine learning-based signal generation on TradeStation and TradingView to optimize trade execution across equities and derivatives.
- Engineered and executed advanced options trading strategies by leveraging volatility modeling, delta-neutral hedging, and stochastic optimization in Excel and Python, achieving a 30% ROI over an eight-month period while maintaining a Sharpe ratio above industry benchmarks.
- Designed data-driven portfolio optimization frameworks using SQL and Python, employing mean-variance analysis, principal component analysis (PCA), and risk parity techniques, dynamically adjusting asset exposure to minimize drawdowns and enhance capital efficiency.
- Conducted high-frequency quantitative research with Python, applying statistical arbitrage, time-series forecasting, and Monte Carlo simulations, generating actionable insights that contributed to a 21% improvement in firm-wide profitability metrics.
Tools: TradingView, TradeStation, Excel, Python, SQL, PineScript