Data Scientist

CVS Health•New York, NY

4d•$111,240 - $222,480•Remote

About The Position

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary: Caremark LLC, a CVS Health company, is hiring for the following role in New York, NY: Data Scientist to develop and implement analytics applications and models to transform data into meaningful information. Duties include: design and develop data solutions using industry leading tools, technologies and best practices to profile data and develop efficient ingestion by sourcing data from PBM, Specialty, Retail, and/or HealthCare business; develop advanced algorithms and statistical predictive models to evaluate scenarios, predict outcomes, and provide usable information on health metrics and potential future outcomes; utilize data mining, data modeling, natural language processing, and machine learning to extract and manipulate data from multiple large data sources and deliver predictive models that inform solutions for in-house teams (i.e. pharmacy pricing, medical costs, risk scores, onboarding) and customer engagement across critical journeys (i.e. calories, heart rate, breast cancer, maternity); utilize data-oriented programming languages and visualization software to explore, analyze, and interpret large volumes of data in various forms and solve complex business problems; visualize and interpret data and create reports, manipulate data using statistical software, and compare models using statistical performance metrics; and support deployment of insights across multiple channels using analysis methods, machine learning, and statistical analyses. Telecommuting available. Multiple positions.

Requirements

Master's degree (or foreign equivalent) in Computer Science, Data Science. Information Technology, Engineering, Analytics, or a related field
Completion of a university-level course, research project, internship, or employment experience in R, Python, or SOL
Completion of a university-level course, research project, internship, or employment experience in NLP (Scikit-Learn, SpaCity, Pytorch, or Spark NLP)
Completion of a university-level course, research project, internship, or employment experience in Data analytics on large data sets in healthcare, business, or retail sector
Completion of a university-level course, research project, internship, or employment experience in Designing data models and solutions for analytical and reporting use cases
Completion of a university-level course, research project, internship, or employment experience in Developing and deploying predictive models or ML systems in a cloud environment (GCP, AWS, or Azure)
Completion of a university-level course, research project, internship, or employment experience in Machine learning operations such as model versioning, model and data lineage, monitoring, model hosting and deployment, scalability, and orchestration
Completion of a university-level course, research project, internship, or employment experience in Feature engineering, model training, hyperparameter tuning, distributed model training, and supervised and unsupervised learning implementation
Completion of a university-level course, research project, internship, or employment experience in Quantitative analysis techniques, including clustering, regression, and pattern recognition
Completion of a university-level course, research project, internship, or employment experience in Developing backend services, performing code reviews, and collaborating with peers on software development solutions
Completion of a university-level course, research project, internship, or employment experience in Contributing to large-scale applications development, data science, or data analytics projects

Responsibilities

Design and develop data solutions using industry leading tools, technologies and best practices to profile data and develop efficient ingestion by sourcing data from PBM, Specialty, Retail, and/or HealthCare business
Develop advanced algorithms and statistical predictive models to evaluate scenarios, predict outcomes, and provide usable information on health metrics and potential future outcomes
Utilize data mining, data modeling, natural language processing, and machine learning to extract and manipulate data from multiple large data sources and deliver predictive models that inform solutions for in-house teams (i.e. pharmacy pricing, medical costs, risk scores, onboarding) and customer engagement across critical journeys (i.e. calories, heart rate, breast cancer, maternity)
Utilize data-oriented programming languages and visualization software to explore, analyze, and interpret large volumes of data in various forms and solve complex business problems
Visualize and interpret data and create reports, manipulate data using statistical software, and compare models using statistical performance metrics
Support deployment of insights across multiple channels using analysis methods, machine learning, and statistical analyses