Aug 2024 – Nov 2024 · 3 mos · United States

Nov 2022 – Aug 2024 · 1 yr 9 mos

• As the Head of Machine Learning at Entrata, I am channeling my comprehensive machine learning experience and related competencies acquired over the years into the multifamily housing industry. Leveraging my familiarity with LLMs and AI, I am driving the development of smarter, more intuitive products. My role involves applying my data science and analytics expertise to propel intelligent decision-making, enhance our product suite, and optimize our clients' experiences. Through a well-rounded understanding of the tech industry and a forward-thinking approach, I continue to innovate and create value in my current role.
• During my time as a data scientist and professor, I've focused on leveraging data science, analytics, and machine learning to create strategic business solutions. My expertise ranges from developing predictive models and managing data pipelines to leading high-performing data science teams.
• I've utilized software tools like Snowflake, Fivetran, dbt, AWS SageMaker, RStudio, and Tableau, coupled with programming languages like SQL, Python and R, to provide actionable insights. I've led the deployment of both traditional and advanced analytics techniques including Agile and Bain RAPIDs delivery methods, natural language processing, and time-series forecasting.

Dec 2020 – Nov 2022 · 1 yr 11 mos

• Reporting to the CTO: Leader of Analytics & Data Science within the EPD (Engineering, Product & Design) group. Responsible and accountable for creating and leveraging the value of Podium data/information assets, including how we use data to increase enterprise, customer, and shareholder value.
• Grow and lead the analytics and data science team from 5 data analysts to now overseeing and a high-performing team of 22 FTE (30 including indirect reports) inclusive of managers, Data Scientists, Data Analysts, and Analytics Engineers.
• The full Analytics & Data Science team structure includes 3 research teams and an Analytics Engineering team. These teams serve all Podium orgs providing key enterprise reporting on core company KPI’s and progress on OKR’s.
• Use a combination of Agile and Bain RAPIDs delivery methods for the creation and implementation of a structured prioritization framework for the team and our stakeholders’, ensuring work is aligned with the strategic goals of each Podium organization and C-Suites.
• Developed career/promotion matrix for Data Analysts, Data Scientists and Analytics Engineers using Radford salary data.
• Lead an enterprise-wide data pipeline rebuild to provide Podium with a modern data stack. This involves deprecation of a 50 terabyte Postgres database (8 followers) with a complete data rebuild in Snowflake. We are now leveraging Fivetran to ingest source data from sources such as Google Analytics, NetSuite, Salesforce etc. using dbt as our transformation tool.
• Develop, lead, and execute key enterprise analytics projects at scale through AWS SageMaker, R Studio Pro Server, RStudio Connect and Tableau.
• Machine learning lead for GTM strategies at Podium with a focus on predicting user value and propensity to buy across Podium’s portfolio of products, customer churn models and lead scoring models.

Oct 2019 – Dec 2020 · 1 yr 2 mos · Provo, Utah

• The Advanced Analytics & Research team is a client facing full service research group that offers white glove statistical solutions to clients. Our team owns the entire research process starting with partnering with clients to identify their research questions and goals, proposing a viable statistical modeling solution, running the analyses and delivering actionable reports/slide decks.
• We leverage the Qualtrics platform along with programming in R and Python which makes us incredibly flexible in what we can do on the research front. The team has a diverse education background which is represented by the fields of Statistics, Education, Marketing, Criminology, Business, Actuarial Science, and Economics.
• Much of our work involves traditional marketing models and techniques such as: Conjoint, MaxDiff, Segmentation, Key Driver Analysis (KDA) along with pricing models such Van Westendorp and Gabor Granger. However, we also use more advanced methods such as time series forecasting, factor analysis, natural language processing, and machine learning models when appropriate.
• Our team is ready to help clients use scientific best practices for any and all research questions they need answered. The Advanced Analytics & Research team helps Fortune 500 and hundreds of other clients a year deliver on their research initiatives.

Feb 2019 – Oct 2019 · 8 mos

Feb 2018 – Jan 2019 · 11 mos

• My main duties involve leading a team of data scientists in developing and implementing DigiCert’s data science roadmap across company organizations. We provide solutions to business problems or create new business opportunities using methods ranging from basic descriptive statistics to automated machine learning models.

Jul 2016 – Feb 2018 · 1 yr 7 mos · American Fork, Utah

• I was part Development/Engineering team and reporting to the Head of Systems Scale. My main objectives aided in the development of Domo features that give our users a complete 360 degree view of their data through visualization, statistical, and machine learning techniques.

Jun 2014 – Jul 2016 · 2 yrs 1 mo · Provo, Utah

• Sociologists study the social world by examining phenomena through a particular theoretical lens (or multiple lenses) and often use quantitative methods to test the validity of theories through hypotheses derived from them. My goal is to teach students the fundamental skills sociologists use to conduct quantitative research via three basic components: (1) how to ask good sociological questions and turn them into research projects with testable hypotheses; (2) how to get the data needed to answer these questions; and (3) how to manage, present, and visualize data to tell a a valid, defensible, and interesting quantitative story. Specifically, learn how to communicate research findings through writing and visualization (with diagrams, tables, and graphs). Major learning outcomes include conducting statistical analyses including univariate, bivariate, and multivariate analysis; learning to code and interpret qualitative data or how to code and prepare quantitative data for statistical analysis; and become critical consumers of information via the development of logical thinking skills.

Aug 2011 – Jun 2014 · 2 yrs 10 mos · Phoenix

• I enjoy teaching statistics and helping students overcome their fear of numbers. Stats is about logic and not just about math. My research focus is social influence and adolescence. Your friends are both good and bad for you in terms of behavior. This also means you are good for some of your friends but bad for others. It's a two-way street.

Jan 2002 – Jun 2005 · 3 yrs 5 mos

• My main duties included conducting social policy research on criminal justice topics and related areas along with preparing state and federal grant applications. I also provided technical assistance and consultation to state and federal funding agencies and grant funded community program managers. This included survey design and oversight; statistical analysis; report writing; coordination of and participation in community-based field research.