Data Science - Senior Advisor

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

CVS Health Enterprise Analytics organization has several teams, Retail Analytics, Pharmacy Personalization Analytics, PBM Finance Analytics and Data Strategy and Engineering, helping lead the effort to transform healthcare and provide better outcomes for patients by leveraging solutions in a particular business analytic area and deliver new insights to leaders that manage the roadmap for enhancements that drive new development on existing or new solutions.

The Data Scientist role within CVS Health is on the front line of driving innovation and directly impacting business decisions. This role falls within the Finance Analytics team and will focus on building & deploying analytic models that help the PBM business meet its client and pharmacy financial guarantees. This team works on drug pricing optimization models using linear and mixed integer programming techniques to optimize drug-level pricing tied to 95 million Americans. The models are designed to meet financial guarantees contracted by Caremark with its clients and pharmacy partners by optimizing drug prices while adhering to several regulatory and business constraints. The outcomes of these models (recommended drug prices) have delivered over $100M in value to Caremark.

Required Qualifications

Bachelor’s Degree in Data Science, Computer Science, Applied Math, Operation Research, Statistics, Health Policy, or other related field with 3+ years of professional experience; Master’s Degree with a minimum of 3+ years of experience; or PhD with 1+ years of experience in:

• Machine Learning or NLP, such as Scikit-Learn, SpaCity, Pytorch, or Spark NLP
• Designing and implementing end-to-end solutions using Machine Learning, Optimization, or other advanced technologies and managing live deployments
• Leading project management activities, including communications within project teams, stakeholder management, and leadership updates
• Extracting actionable insights from the analysis and interpreting outcomes of complex models to present to business audiences including technical, non-technical, and senior leaders
• Preparing data for analysis, working with data engineering team to create modeling dataset, assess completeness and quality of data, and perform feature engineering
• Managing design implementation and cross functional initiatives, and communicating effectively and confidently with business partners, project team members, and senior management
• Working with data and have a strong understanding of analytics and how it is leveraged within the healthcare/retail industry
• 3+ years of experience applying modern machine learning techniques to build predictive models for both classification and regression problems
• 3+ years’ experience with general linear models, including regression techniques, marketing mix models, etc.
• 3+ years of experience coding in Python, R, or other modeling environments
• 2+ year experience with statistical measurements including experimental design, test and control selection, propensity matching, etc.

  Preferred Qualifications

• 3+ years’ experience coding in Python, C++, and optimization packages such as Gurobi, CPLEX, etc.

  Education

• Bachelor’s Degree in Data Science, Computer Science, Applied Math, Operation Research, Statistics, Health Policy, or other related field; or Advanced Degree
• Preferred: Master’s Degree or PhD in Data Science, Computer Science, Applied Math, Operation Research, Statistics, Health Policy, or related field