About

I am an experienced machine learning practitioner and data science leader ready to provide business value to your organization. At Pacific Gas and Electric (PG&E), I am currently serving simultaneously as the technical leader of two engineering teams, a computer vision team and a data engineering team. My data engineering work involves leading 10 data engineers on key company initiatives including the analytics driving decision making in a $25 billion project and fulfillment of metric calculation requirements detailed in California State Senate Bill 884. On the computer vision side, I lead 5 engineers and scientists in developing object detection and classification models as well as their deployment systems on AWS.

In my career, I have:

  • been recognized by the Wall Street Journal for creating computer vision solutions aimed to identify wildfire risk reduction opportunities;
  • designed the first version of the risk framework behind California’s Public Safety Power Shut-offs (PSPS), which received international news attention;
  • led the development of computer vision systems for which PG&E has filed a patent (18/121,348 | 089676-016602/US:ELECTRIC POWER GRID INSPECTION AND MANAGEMENT SYSTEM);
  • received performance evaluations several years in a row that rank me for every performance indicator at the highest level of contribution compared to others in the data scientist job category;
  • leveraged continuous improvement practices to increase active engagement by over 500% to around 70 regular participants in PG&E’s grassroots, voluntary data science community of practice;
  • developed 30+ hours of instructional content to create data science and Python bootcamps attended by a total of 270+ company participants;
  • earned my education at some of the top engineering institutions in the world (Berkeley, Stanford, and Cornell);
  • achieved a 4.0+ grade point average in my computer science master’s degree at Cornell.

I consistently achieve results for my stakeholders by:

  • serving as a kind, humble leader who aims to help his team find autonomy, mastery, and purpose in their work;
  • building trust on my team through establishing psychological safety;
  • fostering a feedback culture to support continuous improvement.

Additionally, I have a proven track record of building and maintaining strong stakeholder relationships by frequently soliciting feedback from those invested in projects early and often throughout a project’s lifecycle. I focus on communicating for understanding and using language appropriate for my target audience.

I believe data science requires a team effort and look forward to collaborating with you on transformative initiatives.

Skills

Artificial Intelligence

I build data products involving predictive, prescriptive, and diagnostic analytics that provide business value. I am experienced in using deep learning, classical machine learning, and optimization methods with large data sets to develop solutions for real business challenges.

Agile and Scrum

I enjoy working in an agile environment, and most of my past experience has been on scrum teams and within organizations implementing the Scalable Agile Framework (SAFe). I have experience leading scrum team ceremonies (stand-up, planning, refinement, retrospective, and sprint review) and look forward to participating in any end-of-sprint demo event that your Agile Release Train may be hosting.

Software Engineering

I am experienced at architecting the software systems behind productionalized data products. I thrive in a collaborative atmosphere complete with pair programming, mobbing, code reviews, and a git workflow. Additionally, I advocate for continuous integration and deployment, good coding practices, as well as systematic approaches to testing software. In the past, I engaged in CodePath's Android Bootcamp, an eight-week program for experienced engineers, and expanded my software engineering knowledge by learning the fundamentals of Android development.

Cloud Computing

My professional experience includes utilizing Amazon Web Services (AWS) as the foundation for my computational work. I am experienced with the AWS SageMaker suite of data labeling, machine learning modeling, and model deployment tools. I am also familiar with AWS services related to building data products (e.g. AWS CloudFormation, CloudWatch, Lambda, ECR, EKS, EC2, RDS, etc). I have also completed the Amazon Web Services Big Data on AWS Training Certification where I covered technologies such as Amazon Athena, EMR, and Kinesis. Additionally, I am skilled in using the PyTorch deep learning framework as well as scikit-learn package and have a familiarity with most other popular Python packages in the data science ecosystem.

Team Leadership

I served as the leader of PG&E’s Data Science Community of Practice (DSCoP), a voluntary, grassroots company-wide organization that facilitates analytics knowledge sharing, community building, and standardization of data science practices across the company. As the leader of the DSCoP, I established an inclusive and psychologically safe environment, thereby increasing active engagement in the organization by over 500% leading to a consistent membership of around 70 individuals. Additionally, I understand the importance of tailoring coaching strategies to a mentee and have coached junior technical colleagues in the past.

Data Science Teaching

I led a core team of 6 data scientists at PG&E to develop the Data Science Lifecycle Bootcamp, a series of 10 classes, each with recorded lecture videos, exercises, office hours, and a live instructional session. Around 20 hours of recorded content was produced, and over 200 employees from across PG&E participated in the bootcamp. Previously, I taught an eight-week introductory Python class to over 70 of my colleagues at PG&E.

Databases

The database technologies I am familiar with include Redshift, Teradata, Oracle, Postgres, MySQL, and Microsoft SQL Server. I often build ETL pipelines, finely tuned queries, and relational data models as well as implement their physical representations to support efficient querying.

Communication Skills

I frequently present data science solutions to large audiences of my data science peers as well as director and executive-level leadership. I am skilled at tailoring presentation material to the expectations of the target audience, and I have presented my work at several industry conferences. At the Association of Edison Illuminating Companies conference in Lake Buena Vista, FL, I was selected as the highest-rated presenter.

For a complete list of skills, please reference my LinkedIn.

Experience

  • Expert Data Scientist, Pacific Gas and Electric Company

    July 2022 - Present

    I am currently serving simultaneously as the technical leader of two engineering teams, a computer vision team and a data engineering team, totaling 15 engineers and scientists.

  • Master's Student in Computer Science, Cornell University

    At Cornell, I focused on machine learning and software engineering.

  • Senior Data Scientist, Pacific Gas and Electric Company

    March 2019 - October 2021

    I collaborated on an award-winning, agile product team recognized by the Wall Street Journal for creating computer vision solutions aimed to identify wildfire risk reduction opportunities.

  • Head of the Data Science Community of Practice, Pacific Gas and Electric Company

    August 2020 - August 2021

    In addition to my main role as a data scientist in machine learning, I served as the leader of PG&E’s Data Science Community of Practice (DSCoP), a voluntary, grassroots company-wide organization focused on facilitating analytics knowledge sharing, community building, and standardization of data science practices across the company. As the leader of the DSCoP, I established an inclusive and psychologically safe environment, thereby increasing active engagement in the organization by over 500% leading to a consistent membership of around 70 individuals. Through the DSCoP, I led a team of data scientists to develop the Data Science Lifecycle Bootcamp, a series of classes focused on teaching best practices at each stage of the data science lifecycle for predictive analytics projects. Over 200 employees from across PG&E participated in the bootcamp classes.

  • Chief of Staff, Pacific Gas and Electric Company

    January 2020 - August 2020

    In addition to my main data science responsibilities, I worked as the chief of staff for my department. In this position, I engaged in departmental administrative and leadership-oriented activities such as planning and facilitating all-hands and leadership team meetings.

  • Data Scientist, Pacific Gas and Electric Company

    August 2017 - March 2019

    I focused on customer-centric problems which required data mining over 1 trillion energy consumption records and building both semi-supervised and unsupervised learning models. During my tenure, I was able to present my research, "Feature Engineering for Time-Series Electric Interval Usage Data," at the Association of Edison Illuminating Companies conference in Lake Buena Vista, FL, and was honored as the highest-rated presenter. Additionally, I also taught an eight-week introductory Python class to over 70 of my colleagues at PG&E.

  • IT Rotational Development Program, Pacific Gas and Electric Company

    August 2015 - July 2017

    I developed professional software engineering skills by collaborating with senior-level engineers to build RESTful web services. I was also able to work on a variety of interesting machine learning projects, learned the Spring and Django web frameworks, and challenged myself to enhance open-source code bases with functionality required for my team's projects.

  • Engineering Intern, Hyundai Motor Manufacturing Alabama, LLC

    June 2014 - August 2014

    My time at Hyundai afforded me the opportunities to assess, formulate, and implement solutions to a number of intriguing problems, including supply-to-line vehicle route optimization and inventory level optimization. I also developed a cost-savings strategy projected to save Hyundai between $90,000 and $420,000 annually and interfaced with teams from across the plant when designing the process improvement.

  • Engineering Student, University of California, Berkeley

    While majoring in Industrial Engineering and Operations Research at the University of California, Berkeley, I engaged in a number of enriching activities including working on research with professors and graduate students, learning about industry through an engineering internship with Hyundai, leading the Institute of Industrial Engineers, instructing Engineering 98, lab assisting for CS 61B, and working as a Residential Computing Consultant in the dorms.

Education

Cornell University

Master of Engineering (M.Eng.), Computer Science

At Cornell, I focused on machine learning and software engineering.

University of California, Berkeley, College of Engineering

Bachelors of Science (B.S.), Industrial Engineering and Operations Research
Fung Institute for Engineering Leadership, Concentration in Entrepreneurship and Technology

Additional coursework completed in computer science.

Stanford University

Graduate Certificate, Information Management

While working full time, I engaged in Stanford's graduate-level computer science classes focused on machine learning, artificial intelligence, and data mining.

Stanford University

Graduate Certificate, Engineering Management

CodePath

Android for Engineers

CodePath's incredible eight-week Android development bootcamp enabled me to deepen my software engineering knowledge by learning the fundamentals of Android development.

University of San Francisco

Certificate, Deep Learning Part I & II
Certificate, Data Science for Marketing

Patents

18/121,348 | 089676-016602/US: ELECTRIC POWER GRID INSPECTION AND MANAGEMENT SYSTEM

I led the development of computer vision systems for which PG&E has filed a patent.

Contact

I would love to hear from you! The best way to contact me about relevant opportunities is through LinkedIn.