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Hi, I'm Ameya! I study computer science at New York University, focusing my coursework in data science, statistics, and machine learning. I am skilled at leveraging my technical background to dissect complex business problems and develop creative solutions that consistently exceed stakeholder expectations. I am currently seeking a data or machine learning role starting in January 2023.

My main languages are Python and SQL, though I have experience with many different languages and frameworks. I have worked closely with all aspects of the data science lifecycle - EDA, ETL, feature engineering, modeling, evaluation, and data visualization. I also have a rigorous mathematical foundation in probability, statistics, linear algebra, and multivariate calculus, which has given me a deep understanding of the tools I use.

I have had two internship experiences, one in software engineering, and another in data science. Through these experiences, I have developed strong collaboration skills, and I am adept at problem framing and communication with both technical and non-technical business leaders.

In my free time, I enjoy reading, singing, and cooking.

During my most recent internship with Intuitive, I:

Collaborated with a team to set up a series of digital product lift analyses with organization-wide impact

• Architected and implemented 2 modular, performance-efficient data foundation components using dbt SQL, prioritizing ease of access for downstream data consumers
• Categorized data items into experimental groups by using Python to discover clusters in sequence data
• Built a Python module from scratch to customize clustering for various data features and parameter settings
• Delivered a final presentation to technical and non-technical senior leaders, including a Scientific Medical Officer and an SVP

Worked with another intern to build a supervised data quality outlier detection model on top of a Snowflake data warehouse

• Arranged meetings with domain experts to identify candidate datasets and gain context about use cases
• Performed exploratory data analysis, ETL, and feature engineering using Python
• Identified bottlenecks and achieved a 5x speedup by writing SQL to offload ETL work from Python to Snowflake
• Presented final results to key project stakeholders, directly linking the technical solution to business value

I have explored data science and machine learning through a number of projects. You can check these out here on GitHub:

• Traffic Simulation Project
• Regularized Subset Selection Project
• COVID-19 Factors Project

I am currently pursuing my M.S. in Computer Science (expected graduation January 2023) at NYU's Courant Institute of Mathematical Sciences. I have also earned my B.A. in Computer Science from NYU, College of Arts and Science. In recognition of my undergraduate academic achievements, I have been elected to Phi Beta Kappa, and I graduated with magna cum laude latin honors.

You can also find me on LinkedIn. Feel free to send me a message anytime - I'm always happy to talk :)