Job Description

Job Description
CVS Health is the nation's premier health innovation company helping people on their path to better health. We are building a new health care model that is easier to use, less expensive, and puts the consumer at the center of their care. Data Science is one of the foundational pillars driving CVS Health into a data centric company. You will be part of a large group of highly accomplished data scientists to help build innovative solutions and manage data using the latest tools and technology. Whether you specialize in Machine Learning, Optimization & Simulations, Statistical Analysis, or Natural Language Processing, you will have ample opportunity to contribute, grow and achieve your best working for Fortune 5s largest healthcare company.

Who we are:
CVS Health Enterprise Analytics organization has several teams, Retail Analytics, Pharmacy Personalization 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.

What you will do:
The Sr. Consultant Data Science role will be a key contributing member of the Pharmacy Personalization team responsible for translating business problems into clear analytical/data science oriented goals and deliver against them. You will be part of a collaborative, high-performing team that leverages cutting edge machine learning techniques across regression/classification, deep learning, NLP and causal inference to deliver direct impact to the bottom & top line of the Pharmacy growth business unit.

The role will be directly responsible for:
Developing machine learning and other advanced models that drive business outcomes across enterprise
Engaging in discussions with key internal and external stakeholders to determine how best to leverage machine learning and advanced analytic methods to support business objectives
Applying appropriate modeling approaches for a given analytic problem (machine learning methods ranging from regression methods, decision trees, deep learning, NLP techniques, uplift modeling; operations research; statistical modeling such as multivariate techniques)
Partnering with Data Engineering peers in identifying and designing core modeling pipelines that will ensure scalable deployment of ML models
Contributing to the wider Enterprise data science community by sharing their knowledge of machine learning algorithms and analytics methods, participating in journal clubs
Presenting their work to both technical and non-technical audience in a coherent way to further influence decision making using a analytics driven approach
Performing ad-hoc analyses that mines messy data to deliver a clear data driven story

Required Qualifications
Required Qualifications:

Bachelors Degree with 2+ years professional experience, or Masters in any of the following fields:
Computer Science, Data Science, Applied Math, Engineering, Operation Research, Statistics, Epidemiology, or other related quantitative fields.

Professional Experience includes the following areas:

Expert level proficiency with common modeling tools and frameworks, e.g. Python, R, Scala, TensorFlow, etc.
Proficient with model pipeline technologies like Airflow, MLFlow, MLOps, Kubeflow etc.
Proficiency with tools to automate CI/CD pipelines (e.g., Jenkins, GIT, Control-M)
Hands-on experience manipulating data on big data environments using state of the art technologies like PySpark, Hive etc.
Experience with cutting edge ML tools & languages, both open source and proprietary eg.TensorFlow, PyTorch, PySpark etc.
Excellent communication skills and adept at explaining complex technical concepts to both technical and non-technical audiences. Ability to parse business questions and identify clear analytical goals from them.
Ability to understand data management and model productionalization best practices
Experience with data visualization that help tell a deeper story of data distributions and improve explainability of the models.

Preferred Qualifications
Experience with cloud technologies like MS Azure, GCP, AWS etc
Productionalized one or more ML applications on big data servers

Education
Bachelors Degree in Computer Science, Data Science, Applied Math, Engineering, Operation Research, Statistics, Epidemiology, Public Health or other related quantitative fields.
Preferred: Masters Degree in Computer Science, Data Science, Applied Math, Engineering, Operation Research, Statistics, Epidemiology, or other related quantitative fields

Business Overview
At CVS Health, we are joined in a common purpose: helping people on their path to better health. We are working to transform health care through innovations that make quality care more accessible, easier to use, less expensive and patient-focused. Working together and organizing around the individual, we are pioneering a new approach to total health that puts people at the heart.

We strive to promote and sustain a culture of diversity, inclusion and belonging every day. CVS Health is an equal opportunity and affirmative action employer. We do not discriminate in recruiting, hiring or promotion based on race, ethnicity, sex/gender, sexual orientation, gender identity or expression, age, disability or protected veteran status or on any other basis or characteristic prohibited by applicable federal, state, or local law. We proudly support and encourage people with military experience (active, veterans, reservists and National Guard) as well as military spouses to apply for CVS Health job opportunities.