Delivers against the overall data science strategy to drive in-store and digital merchandising, marketing, customer loyalty, and operational performancePartners with product development to define requirements which meet system and customer experience needs for data science projects.Partners with Merchandising, Supply Chain, Operations and customer insights to understand the journey that will be improved with the data science deliverables.Delivers end-to-end data science pipelines including custom algorithms, statistical models, machine learning and artificial intelligence functions to meet partner needs.Partners with product development and technology teams to deploy pipelines into production MLOps environment following Safe Agile methodology.Drives adoption and usage of analytical products and models.Anticipates future business needs and identify opportunities that make substantial difference for organization, and lead the development of analytics initiatives.Responsible for defining, documenting and following best practices for ML/AI development at Meijer.Owns communication with data consumers (internal and external) to ensure they understand the data science products, have the proper training, and are following the best practices in application of data science products.Defines and analyzes Key Performance Indicators to monitor the overall health and measure value of the data products..Identifies and scopes, in conjunction with IT, the architecture of systems and environment needs to ensure that data science systems can deliver against strategy.Builds and maintains relationships with key partners, suppliers and industry associations and continue to advance data science capabilities, knowledge and impact.

• Replaced our off-the-shelf forecast models with custom neural networks.• Presented custom neural network to managers interested in imminent launch.• Using Microsoft Power Apps, built and maintained an app for managing line haul drivers around the country.• Became the company’s lead in-house expert on Power Apps, helping other departments build and maintain apps.• Led and advised on data projects related to pricing, capacity, forecasting, and management.• Regularly consulted by team members for troubleshooting coding and statistics.• Participated in weekly education seminars and project management meetings with larger team of data scientists, engineers, and analysts, as well as weekly one-on-ones with direct supervisor.

Software Skills R A computer language and software environment for statistical analysis and data management. -For visualization: coefplot, colorspace, cowplot, directlabels, effects, ggalluvial, ggplot2, ggpubr, igraph, lattice, magick, and plotly -For advanced analysis: lme4 (for mixed models), mlogit (for random utility discrete choice models), and VGAM (for categorical data analysis) -For advanced data processing: dplyr and reshape2 -For 3d data, 3d printing, and terrain: elevator, rayshader, rgdal, rgl, scatterplot3d, and sjPlot -For time series and survival analysis: forecast, vars, and flexsurv 4 Python An interpreted, high-level and general-purpose programming language. -TensorFlow (for deep learning) -Keras (for deep learning) -NumPy (for large, multi-dimensional arrays and matrices) -pandas (for data manipulation and analysis) Simulation of Urban MObility (SUMO) An open source, portable, microscopic and continuous multi-modal traffic simulation package designed to handle large networks. SQLA database management programLATEX A typesetting programFor application of these programs, see dissertation description under LinkedIn "Projects"

I composed the syllabus and all lesson plans and gave lectures to 40+ students in "Introduction to Comparative Science" in winter and spring quarters 2019 and 2020.

Acted as TA for Undergraduate Courses at UC Davis:Introduction to Comparative Politics Fall 2019 & Fall 2020 The Scientific Study of Politics Spring 2016, Fall 2018, & Winter 2020 Quantitative Analysis of Political Data Spring 2019 American Foreign Policy Winter 2016 The Scientific Study of War Fall 2015Also as TA for the 1st-year Political Science Graduate Statistics Sequence (fall 2016, winter 2017 & spring 2017 I taught). This is a prestigious TA position awarded to a current graduate student to teach incoming graduate students a three-quarter statistics sequence to ensure that these graduate students are ready for advanced coursework in the statistically-rigorous UCD political science program; led weekly sections teaching them R.

I acted as an instructor and teaching assistant for the Masters of Public Affairs program at UC Berkeley in summer 2017; taught adults ages 22-50. Courses taught and assisted with include:• Research Methods• Inferential Statistics • Risk and Decision Models • Accounting and Budgets

I was a TA for Judicial Politics, an undergraduate course at the University of Utah, during my Masters program.