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Table of Contents Work Experience Education Projects Skills Extracurricular

Work Experience

Applied AI Engineer

BASF Corporation

09/2023 — present

BASF is a Global Fortune 500 company, the largest chemicals company in the world, and a leader in sustainable manufacturing. My ambition is to be a change agent that transforms chemical production with artificial intelligence to make plant operations safer and more efficient. My highlights:

Tools and Platforms - Microsoft Azure, Kubernetes, Docker, MLflow, Python, Dagster, FastAPI, MongoDB, PostgreSQL
Value owner of a software product aimed at training and deploying machine learning models across production sites; secured $250K funding, led team in development using agile methodology, designed the microservices architecture and ML pipelines, evaluated and explored ML design patterns, deployed to Azure Kubernetes Services, and implemented aspects of ML pipelines and API services.
Core developer of a GenAI Copilot product for production plants; designed data management and event processing, implemented LLM-based classification of document types, drove rollout efforts to plants in NA

Data Science Professional Development Program

BASF Corporation

08/2021 — 08/2023

I am participating in the company's professional development program for data science, which is a rotational program designed to produce data science leaders. In my first rotation, I worked in AI Solutions for Sales, Marketing, and Customer Engagement, where I worked as a product owner for a market intelligence product to make strategic business development more data-driven. In my second rotation, I worked on AI chemical process modeling for a chemical business. In my final rotation, I worked for Production AI leading efforts to develop new capabilities for digital twins of production plants. My highlights:

Tools and Platforms - Databricks, Microsoft Azure, Delta Lake, MLflow, PowerBI, Python, Streamlit, Dagster
Managed team of 4 developers in building a proprietary market intelligence product for internal clients in strategic business development; bridged business needs and technical development by communicating with stakeholders and translating business problems into tangible solutions
Developed a digital twin of a production unit, enabling operations to monitor quality, simulate hypothetical scenarios, and receive real-time recommendations. Estimated $4M savings potential
Architected a machine learning system that can produce a 10-hour forecast of product quality with 98% accuracy and an F1-score of 0.97

Data Science Intern

BASF Corporation

06/2020 — 08/2020

I was the company's first data science intern in their professional development program. I also received the highest performance rating for my contributions.

Developed cloud application with productionized machine learning, data management, and automated data pipelining using SciKit-Learn, PostgreSQL, Kubernetes, and Gitlab which will save $500K per year on plant operation expenses
Applied weak supervision AI, NLP, and logistic regression using Snorkel, VADER, and Sci-Kit Learn on the customer survey dataset to identify the most insightful responses out of 20,000+ that should be prioritized by customer service, thus improving the efficiency of reviewing customer feedback
Presented weak supervision theory and company-specific use cases to an audience of 45 BASF technical experts, including PhDs and Digitalization leaders

Education

The University of California, Berkeley

Master's in Data Science

2022 — 2024

GPA: 4.0
Coursework: Research Design, Statistics, Probability Theory, Data Engineering, Machine Learning, Natural Language Processing and Deep Learning, Machine Learning Systems, Data Strategy, Capstone
Achievements: One of 6 teams (out of 33) to advance to capstone showcase.

The University of Texas at Austin

Bachelor's in Chemical Engineering, Minor in Computational Science

2016 — 2021

GPA: 3.65
Coursework: statistics, object-oriented programming, databases, data structures & algorithms, machine learning, linear algebra, differential equations
Achievements: 1st Place at Spring 2020 Demo Day, 2x Undergraduate Research Fellowship, 2nd out of 16 in case competition, 2nd out of 7 in pitch competition, 4x University Honors, 4th out of 12 in engineering competition

Projects

See projects

Skills

Check out my project tags page to see which technical skills I’ve demonstrated in my projects.

Programming

Python

95%

Git

90%

Docker

80%

Azure

75%

Kubernetes

70%

SQL

65%

Linux

60%

Spark

40%

30%

Disciplines

Machine Learning

90%

Machine Learning Engineering / MLOps

85%

Generative AI

80%

Software Design

70%

Product Strategy

65%

Data Engineering

60%

Backend Development

60%

Statistics

50%

Extracurricular

Product Strategy Instructor/Mentor

Convergent

05/2020 — 05/2021

Convergent is an organization at UT Austin and UC Berkeley with a mission to educate students on how to turn ideas into minimum viable tech products. During my year with Convergent, I taught product strategy to over 30 students and mentored 6 build teams in developing AI-powered and productivity products. Two of my build teams won awards at Convergent's Demo Day (Best Overall and Best Business).

Founder and President

Texas Solar Energy Group

09/2018 — 05/2020

UT Austin is one of the world's leading universities in energy research. When I was a student, I was interested specifically in solar energy, but I realized there were few opportunities for undergraduate students to get involved. To fill the gap, I founded Texas Solar Energy Group to provide a space for students interested in solar energy to conduct student-led research and engineering projects on the topic. During my time as President, the organization grew to over 30 student members, received over $5,000 in funds from grants and awards, established partnerships with several solar energy startups, won the Undergraduate Research Fellowship twice, placed 2nd out of 16 teams at an energy case competition, and placed 2nd out of 7 teams at an alternative energy pitch competition.