Aug 2024 – Jul 2025 · 11 mos

• Led a team in the creation, strategy and execution of an Agentic AI initiative which leverages advances in GenAI to build efficiencies in our Claims organization (LangChain, LangGraph, LLMs)
• Managed a team of consultants to design, execute and evaluate a GenAI document extraction product which has substantially reduced the amount of time that claims specialists spend assessing certain documents

Dec 2023 – Aug 2024 · 8 mos

• Led the unification of disparate product data sources to support forecast modeling and business intelligence
• Implemented state-of-the-art forecasting models to predict core business KPIs
• Interfaces with business partners across the organization to identify product requirements and drive engagement

Oct 2022 – Dec 2023 · 1 yr 2 mos

• Drove product innovation through leading stakeholder research to identify new opportunities within the organization, leading the development of a new data-driven decision management tool for internal use
• Routinely collaborates with engineers, product managers, and business stakeholders

Jan 2022 – Oct 2022 · 9 mos

• Led a project team to develop and deploy a machine learning and data driven risk advising product, including collaboration with engineers, UX designers, underwriters, and product teams
• Acted as a Data Science Team Lead where I support a team of 4 data scientists through biweekly 1-on-1 meetings, weekly team meetings, and an internal team enrichment project

Jun 2021 – Jan 2022 · 7 mos

• Trained and deployed multiple computer vision models to identify hazards in customer-submitted photos using ResNet backbones
• Developed 2 internal Slackbots using AWS lambda to automate previously manual work
• Mentored 2 summer interns by holding weekly 1-on-1 meetings, advising on project work, and coaching on career opportunities

Sep 2020 – Jun 2021 · 9 mos

• Developed an internal AutoML architecture for training and deploying models at scale across the organization. I presented this work at the 2021 IEEE DSAA conference
• Leveraged NLP methodologies such as TF-IDF to improve label extraction from free-text fields
• Implemented an evaluation rubric for the coding challenge completed by candidates as part of their interview to promote equitable hiring practices

Jul 2019 – Sep 2020 · 1 yr 2 mos · Greater Chicago Area

• Performed uplift modeling for a clothing retailer to optimize the level of personalized discount amounts to drive sales while minimizing losses to discounts
• Built and maintained data pipelines for extracting and transforming survey data for presentation in a client-facing dashboard application
• Performed advanced analysis on national and global survey data for a global technology company to understand public sentiment and behavior of their customers

Mar 2016 – Jun 2019 · 3 yrs 3 mos · Greater Chicago Area

• Tutored students in science, math, and computer science courses
• Developed strong communication skills necessary for teaching complex topics

Sep 2015 – May 2019 · 3 yrs 8 mos · Chicago, Illinois

• Applied deep learning through transfer learning from convolutional neural networks to classify 78 breast lesion images using Keras and Python, resulting in a first-authored publication
• Collaborated with MD Anderson Cancer Center to perform temporal sequence pattern detection with Keras and Python using long short-term memory networks to classify lesions on 848 images

Jul 2015 – Sep 2015 · 2 mos · Chicago, Illinois

May 2014 – Aug 2014 · 3 mos · Boston, MA

• Awarded a fellowship to execute a research project over one summer at Massachusetts General Hospital under Dr. Alexei Trofimov
• Analyzed x-ray images from proton therapy treatment of 68 ocular melanoma patients to assess fidelity of dose and set-up variations
• Results were presented at the 2014 AAPM conference
• Presented the results to the Radiation Oncology department at Massachusetts General Hospital
• Poster won second prize at the 2015 CUWiP UCSC conference
• One of only 11 students selected nationwide to participate in this highly selective program

Aug 2013 – May 2014 · 9 mos · Greater Los Angeles Area

• Received the Undergraduate Research Associates Program grant to work in Dr. Vitaly Kresin's nano cluster physics laboratory.
• Used helium nano droplets to study the fragmentation of chemical compounds
• Created a manual for start-up and shut-down of a vacuum chamber and helium beam in order to improve efficiency and safety, and minimize risk

Aug 2012 – May 2013 · 9 mos · Los Angeles, CA

• Received a Student Opportunities for Academic Research grant
• Solved differential equations to model the time-evolution of quantum hamiltonians in a heat-bath system

May 2013 – Aug 2013 · 3 mos · Berkeley, CA

• Received internship to work with Dr. Peter Nugent and the Computational Cosmology Center at the Lawrence Berkeley National Laboratory
• Used machine learning software for target selection in Dark Energy Camera images for the upcoming Dark Energy Spectroscopic Instrument sky survey
• Presented findings to researchers at Lawrence Berkeley National Laboratory Poster Session

May 2012 – Aug 2012 · 3 mos · Seattle, WA

• Ocean Physics and Dynamics Field Work
• Calibrated oceanography instruments
• Deployed instruments in the Pacific Ocean

Jan 2010 – Aug 2011 · 1 yr 7 mos · Greater Seattle Area

• Climate Change Internship
• Studied the public's perception of climate change through subject interviews
• Presented research findings at the Pacific Science Center to high school students
• STEM OST Intern with Science on Wheels
• Traveled to outside-of-school programs in the Seattle area to present STEM lessons to children ages 6-12
• Discovery Corps Program
• Engage with museum guests to interact with exhibits and answer questions
• Assist with operations, including butterfly house and planetarium admissions