Humana
Senior Associate, Marketing Data Scientist (Pharmacy)
Humana, Fort Lauderdale, Florida, us, 33336
Become a part of our caring community and help us put health first
As a Senior Data Scientist, Pharmacy Analytics, you’ll lead analytical efforts that support Humana’s pharmacy marketing and operations. You’ll deliver insights that drive strategic decisions, improve member outcomes, and optimize pharmacy engagement.
This role is ideal for someone who thrives in a data-driven environment and enjoys solving complex business challenges.
Role Responsibilities You’ll lead the development of analytics that inform pharmacy strategy and performance.
Conduct advanced analyses to evaluate pharmacy marketing campaign effectiveness and member behavior
Leverage dashboards & reporting tools for marketing leadership and stakeholders
Collaborate with cross-functional teams to align analytics with strategic goals
Translate complex data into clear, actionable insights
Mines, cleans and analyzes data from company databases and external data sources to build prediction of marketing goals, report on campaign performance over time by each channel.
Develop custom machine learning models such as segmentation, multi touch attribution, churn models etc.
Use predictive modeling to bring insights into Humana member experiences utilizing Regression, Random Forest, XG Boost models, clustering, text mining for revenue generation, and other business outcomes.
Conduct a power analysis, do hypothesis testing, develop marketing A/B test design, support implementation of the tests and present the statistical findings of the test to our business partners.
Develop processes and tools to monitor and analyze model performance and data accuracy.
Coordinate with different functional teams to implement models and monitor outcomes.
Test Design and Analysis: responsible for valid test design, appropriate sample sizing and setup to ensure results are statistically significant and insights are generated. Responsible for advocating and building the discipline for continual testing, measurement, and iteration.
Use mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions
Use your skills to make an impact Required Qualifications
Bachelor's degree in data analytics, Pharmacy, Business, healthcare, related quantitative field OR 3–5 years of data analytics or data science experience
3+ years of demonstrated proficiency in SQL, Python, or R for data analysis and modeling
3+ years, strong experience with data visualization tools (e.g., Tableau, Power BI)
3+ years of experience with setting up causal inference experiments
Experience in developing, maintaining, and collecting structured and unstructured data sets for analysis and reporting
Be able to create reports, projections, models, and presentations to support business strategy and tactics
3+ years and knowledge of predictive modeling and segmentation techniques
Preferred Qualifications
Master’s degree in a quantitative or healthcare-related field
Familiarity with HIPAA and healthcare compliance standards
Experience with Snowflake/ Databricks
Marketing experience a plus
Experience with Adobe Analytics
Strong experience leveraging data visualization tools (e.g., Tableau, Power BI)
Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
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As a Senior Data Scientist, Pharmacy Analytics, you’ll lead analytical efforts that support Humana’s pharmacy marketing and operations. You’ll deliver insights that drive strategic decisions, improve member outcomes, and optimize pharmacy engagement.
This role is ideal for someone who thrives in a data-driven environment and enjoys solving complex business challenges.
Role Responsibilities You’ll lead the development of analytics that inform pharmacy strategy and performance.
Conduct advanced analyses to evaluate pharmacy marketing campaign effectiveness and member behavior
Leverage dashboards & reporting tools for marketing leadership and stakeholders
Collaborate with cross-functional teams to align analytics with strategic goals
Translate complex data into clear, actionable insights
Mines, cleans and analyzes data from company databases and external data sources to build prediction of marketing goals, report on campaign performance over time by each channel.
Develop custom machine learning models such as segmentation, multi touch attribution, churn models etc.
Use predictive modeling to bring insights into Humana member experiences utilizing Regression, Random Forest, XG Boost models, clustering, text mining for revenue generation, and other business outcomes.
Conduct a power analysis, do hypothesis testing, develop marketing A/B test design, support implementation of the tests and present the statistical findings of the test to our business partners.
Develop processes and tools to monitor and analyze model performance and data accuracy.
Coordinate with different functional teams to implement models and monitor outcomes.
Test Design and Analysis: responsible for valid test design, appropriate sample sizing and setup to ensure results are statistically significant and insights are generated. Responsible for advocating and building the discipline for continual testing, measurement, and iteration.
Use mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions
Use your skills to make an impact Required Qualifications
Bachelor's degree in data analytics, Pharmacy, Business, healthcare, related quantitative field OR 3–5 years of data analytics or data science experience
3+ years of demonstrated proficiency in SQL, Python, or R for data analysis and modeling
3+ years, strong experience with data visualization tools (e.g., Tableau, Power BI)
3+ years of experience with setting up causal inference experiments
Experience in developing, maintaining, and collecting structured and unstructured data sets for analysis and reporting
Be able to create reports, projections, models, and presentations to support business strategy and tactics
3+ years and knowledge of predictive modeling and segmentation techniques
Preferred Qualifications
Master’s degree in a quantitative or healthcare-related field
Familiarity with HIPAA and healthcare compliance standards
Experience with Snowflake/ Databricks
Marketing experience a plus
Experience with Adobe Analytics
Strong experience leveraging data visualization tools (e.g., Tableau, Power BI)
Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
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