Senior Data Scientist - Specialty Operations Optimization

Bring your heart to CVS Health. Every one of us at CVS Health shares a single, clear purpose: Bringing our heart to every moment of your health. This purpose guides our commitment to deliver enhanced human-centric health care for a rapidly changing world. Anchored in our brand — with heart at its center — our purpose sends a personal message that how we deliver our services is just as important as what we deliver.
 
Our Heart At Work Behaviors™ support this purpose. We want everyone who works at CVS Health to feel empowered by the role they play in transforming our culture and accelerating our ability to innovate and deliver solutions to make health care more personal, convenient and affordable.

Position Summary

• Lead development of complex ML pipelines and statistical models to grow business value by improving CVS Specialty pharmacy resource forecasting
• Leverage technology depth to engage with key leaders across the enterprise to identify new applications of artificial intelligence in CVS Specialty pharmacy
• Collaborate with business partners to understand their problems and goals, develop predictive modeling, statistical analysis, data reports and performance metrics
• Develops and participates in presentations and consultations to existing and prospective constituents on analytics results and solutions
• Interacts with internal and external peers and managers to exchange complex information related to areas of specialization
• Use strong knowledge in algorithms and predictive models to investigate problems, detect patterns and recommend solutions
• Use strong programming skills to explore, examine and interpret large volumes of data in various forms

Required Qualifications

• 3+ years of experience with advanced machine learning techniques, such as deep learning, natural language processing, computer vision and reinforcement learning
• 3+ years of expertise using data science, programming, and visualization tools such as Snowflake, SQL, cloud-based ML Ops tech stack and Tableau
• Domain expertise in time series analysis, demand forecasting and supply chain analytics having mastered the techniques across spectrum of complexity – Tree based models, ARIMA, deep learning based time series models
• Expertise in application of optimization techniques (Mixed Integer, Linear Programming) and simulation
• Prior experience using and managing projects leveraging Cloud technologies (Azure, GCP, AWS, Databricks)
• Expert level programming skills in Python or R
• Ability to engage with senior business stakeholders, execute level communication and influencing skills
• Highly motivated individual willing to upskill with an ability to work in an extremely fast paced environment both individually and with a team

Preferred Qualifications

• Demonstrates strong ability to communicate technical concepts and implications to business partners
• Anticipates and prevents problems and roadblocks before they occur
• Strong knowledge of advanced analytics tools and languages to analyze large data sets from multiple data sources
• Demonstrates proficiency in most areas of mathematical analysis methods, machine learning, statistical analyses, and predictive modeling and in-depth specialization in some areas
• Robust data management and reporting skills, understanding of deploying machine learning models in real time production environments including cloud (Azure, AWS, GCP), Spark-based systems, etc.

• Highest level of attention to detail when working within legal and compliance
  regulations, primarily around HIPAA, patient safety work product, and attorney/client privilege while working with sensitive, confidential, and protected data. Strong analytics and data skills including solid training in statistics and data analysis, understanding of data management and visualization, ability to interpret outcomes of machine learning models

• 3+ years of hand-on experience building neural networks in Tensorflow, Pytorch or Keras for processing structured and unstructured data for applications across industry domains.
• Robust data management and reporting skills, understanding of deploying machine learning models in real time production environments including cloud (Azure, AWS, GCP), Spark-based systems, etc.

Education

Bachelor's degree or equivalent work experience in Mathematics, Statistics, Computer               Science, Business Analytics, Economics, Physics, Engineering, or related discipline.

Master’s degree or PhD preferred

Pay Range

The typical pay range for this role is:

$106,605.00 - $206,000.00

This pay range represents the base hourly rate or base annual full-time salary for all positions in