Tejas Linge
Summary
Proactive and ambitious professional with a keen analytical mindset and a meticulous attention to detail. Leveraging 2 years of experience in Quantitative Analysis and Data Science, adept at optimizing data pipelines and enhancing processes for large datasets. Demonstrates excellent technical proficiency and a proactive approach to problem-solving. Passionate about leveraging data-driven insights to drive impactful decisions and achieve organizational objectives.
Overview
2
2
years of professional experience
1
1
Certification
Work History
Quant - Team Lead
New Berry Capital
Mumbai
01.2024 - Current
- Leading all aspects of portfolio management, from strategy conception to execution, for two distinct portfolios totaling 5 Cr.
- Managing a dynamic team of 6 professionals, fostering collaboration and ensuring alignment with organizational goals.
- Collaborate closely with fund managers to deeply understand and refine both intra-day Options directional (leveraging technical indicators such as Bollinger Bands, MACD, Keltner Channel, etc) and non-directional (Delta-hedging strategies like Spreads and Straddles) trading strategies
- Created a market-neutral portfolio that has generated 17% returns in the past 3 months
- Leveraged advanced methodologies including multiprocessing and decision trees to optimize pipelines, drastically reducing back-testing and portfolio creation time by 98% for 600 million parameters.
- Continuously developing and refactoring reusable Python pipelines to efficiently process large datasets, driving operational excellence and performance enhancement.
Associate Data Scientist
Pixis
Bangalore
11.2021 - 12.2023
- Engineered data pipelines, facilitating seamless data collection, preprocessing, manipulation, and aggregation. Achieved a ~90% reduction in API calls, leading to substantial cost efficiencies.
- Worked iteratively on Prompt and Engineering Pipelines, heavily leveraging LLMs like GPT-3, ChatGPT, and Bard
- Led development of 6 core products and data-driven insights using historical data for Google/Facebook Text and Image Ads - resulting in a 76% higher ROI of new ads. Applied AWS Rekognition for Image Analysis
- Created descriptive statistical dashboards to improve ROI on Google Campaigns by 42%. Implemented K-Means and Agglomerative Clustering, to perform Data Segmentation, remove noise, and enhance data-driven insights
- Utilized Random Forest and built predictive models for performance forecasting of new Ads with 79% accuracy
- Managed 10 monthly KPI reports of clients with a total marketing budget of ~$80M. Generated data-driven insights to improve the average conversion rate of SEARCH campaigns by 72%
Education
B.Tech - Electronics And Telecommunication Engineering
Vishwarkarma Institute of Information Technology
Pune06-2022
Skills
- Python
- Quant Development
- Machine Learning
- Derivatives Trading
- Data Engineering
Certification
- NISM Series-VIII: Equity Derivatives
References
References available upon request.
Timeline
Quant - Team Lead
New Berry Capital
01.2024 - Current
Associate Data Scientist
Pixis
11.2021 - 12.2023
B.Tech - Electronics And Telecommunication Engineering
Vishwarkarma Institute of Information Technology
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