Data Scientist - Predictive Analytics

McKesson•Columbus, OH

About The Position

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you. CoverMyMeds, part of McKesson, helps patients access the medications they need by solving complex medication access and affordability challenges. Through data, automation, and expert intervention, we support providers, pharmacies, payers, biopharma, and—most importantly—patients. Role Overview We are seeking a Data Scientist to support forecasting and demand planning initiatives, including volume and contact center forecasting. This role focuses on developing and enhancing statistical and predictive models to improve forecasting accuracy, workforce planning, and operational decision‑making. You will work closely with cross‑functional partners in operations, workforce management, and analytics to translate complex data into clear, actionable insights that drive business outcomes.

Requirements

Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or equivalent experience
4+ years of experience applying advanced analytics to solve business problems
Strong experience (4+ years) with forecasting and statistical modeling, including time‑series analysis
Proficiency (4+ years) in Python (required) and experience with R
Advanced (4+ years) SQL and experience working with large datasets
Hands‑on experience (4+ years) with data modeling, statistics, and applied mathematics
4+ years' Experience using Databricks, Snowflake, or similar cloud‑based data platforms
Ability to analyze trends, mine complex transactional data, and troubleshoot analytical issues
Experience creating analytics‑driven visualizations and presenting insights clearly
Comfortable working with moderate autonomy in a collaborative, cross‑functional environment
Must be authorized to work in the U.S. (no sponsorship available)

Nice To Haves

Experience with contact center analytics, workforce management, or operational forecasting
Background in healthcare, pharmaceutical, biopharma, or insurance environments
Exposure to advanced techniques such as machine learning, regression, segmentation, NLP, or decision trees
Familiarity with Azure, automation, version control, or model deployment workflows
Strong communication, presentation, and stakeholder‑management skills
Intellectual curiosity, comfort with ambiguity, and desire to continuously learn

Responsibilities

Analyze large, complex datasets to improve forecasting accuracy and operational planning
Develop, maintain, and enhance statistical and predictive models for volume and contact center forecasting
Apply time‑series forecasting, predictive modeling, and scenario planning techniques to anticipate demand
Partner with stakeholders to identify opportunities to improve productivity, performance, and customer experience
Create and present clear data visualizations and insights for technical and non-technical audiences
Communicate forecasting results and recommendations to internal teams and occasional external partners
Support optimization of staffing and workforce planning models with guidance from senior team members