Senior Data Scientist - Payor Relations

Senior Data Scientist - Payor Relations

This job is no longer open

Job Description
The Data Science and Optimization team is responsible for development of industry-leading analytics solutions to enable a roadmap that drives the technology development & innovation, while delivering high-quality and high-value solutions. This position will be reporting to the Senior Manager of Data Science.
The Sr. Data scientist will leverage their deep technical and institutional expertise to drive ML solutions in payor relations and retail analytics while developing products:
• That optimize the drug prices at 9700+ pharmacy locations
• That enhance customer experience in our retail pharmacy stores.

The ideal candidate should have deep AI/ML expertise and a collaborative mindset to inspire the team, align cross-functional stakeholders, and deliver efficient result. They should be able to leverage technology to engage with business stakeholders across the enterprise to work on new applications of data science in payor relations domain. They would be responsible for routine testing of ML solutions to ensure results are consistent with business requirements.
We are looking for a candidate that has an ownership mindset to lead a workstream with minimal supervision and has the energy to inspire new initiatives by applying state-of-the art ML/AI and optimization techniques for generating higher impact.
The candidate must be experienced in developing end to end solutions across the data science product pipelines with adequate knowledge in fields of data engineering, ML modeling, visualization, server deployments, distributed database management, MLOps and statistics.
Responsibilities include

• Lead development of complex ML pipelines and statistical models to grow business value by improving our pricing operations
• Leverage technology depth to engage with key leaders across the enterprise to identify new applications of artificial intelligence in payor relations
• Gather business requirements from various stakeholders and lead analysis of massive datasets to synthesize strategies and tactics to solve complex problems
• Conduct or coordinate appropriate testing of data/ML solutions to ensure results are consistent with business expectations
• Present and communicate meaningful insights obtained from ML model results to technical and non-technical audiences including internal stakeholders and senior leadership

Pay Range
The typical pay range for this role is:
Minimum: 90,000
Maximum: 180,000

Please keep in mind that this range represents the pay range for all positions in the job grade within which this position falls. The actual salary offer will take into account a wide range of factors, including location.

Required Qualifications
• 3+ years of relevant experience working in data science with a track record of delivering insights and business impact
• 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
• 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.
• Prior experience using and managing projects leveraging Cloud technologies (Azure, GCP, AWS, Databricks)
• Expert level programming skills in Python or R

Preferred Qualifications
• 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
• Domain expertise in time series analysis, demand forecasting and pricing analytics having mastered the techniques across spectrum of complexity – Tree based models, ARIMA, deep learning based time series 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.
• Expertise in application of optimization techniques (Mixed Integer, Linear Programimg) and simulation.
• 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.

Education
• Bachelor’s Degree required
• Master’s degree or PhD in Statistics, Computer Science, Mathematics, or related STEM field is preferred.

Business Overview
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.
We strive to promote and sustain a culture of diversity, inclusion and belonging every day.
CVS Health is an affirmative action employer, and is an equal opportunity employer, as are the physician-owned businesses for which CVS Health provides management services. We do not discriminate in recruiting, hiring, promotion, or any other personnel action based on race, ethnicity, color, national origin, sex/gender, sexual orientation, gender identity or expression, religion, age, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.
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