Olivia Hebner

Olivia Hebner

Data Science Manager @Summit

Washington, DC, US
EMAILS
o••••••••@summitllc.us
MOBILE NUMBERS
+91 *********19

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WORK HISTORY

Jan 2024 — Present

Data Science Manager @Summit

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Washington, DC, US

EDUCATION

2015 — 2017

University of Memphis

Master of Arts - MA, Economics

2011 — 2015

Rhodes College

Bachelor of Arts - BA, Economics

ABOUT OLIVIA HEBNER

Olivia Hebner is a Data Science Manager at Summit Consulting with over eight years of experience leading teams in applied data science, analytics, and application development for federal and commercial clients. She specializes in modernizing complex, high-stakes analytics—often built in legacy tools such as Excel, Stata, and SAS—into scalable, auditable data products using open-source technologies including R and Python, supported by cloud-based infrastructure on AWS and Azure.Olivia has deep experience designing and executing complex data science projects spanning predictive modeling, statistical programming, survey analysis, and data engineering. Her technical background includes regression and time-series modeling, data wrangling and analysis using Python (Pandas, NumPy, scikit-learn) and R (dplyr, ggplot2, stringr, Shiny), SQL-based data workflows, and the development of both static and interactive visualizations that support decision-making and drive business outcomes.A key focus of Olivia’s work is bridging the gap between data science and software development. She regularly partners with engineers to move analyses out of notebooks and into production-ready systems, delivering dashboards, applications, APIs, and automated pipelines that stakeholders can rely on day to day, while meeting strict requirements around compliance, transparency, and auditability.In addition to her technical leadership, Olivia is passionate about mentoring data scientists, developing shared methodologies, and building data science communities of practice. She excels at translating complex analytical concepts for both technical and non-technical audiences and designing clear, accessible outputs that help analytics reach their full impact.

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