Sr. Decision Scientist

CVS Health•New York, NY

1d•$109,491 - $173,040•Remote

About The Position

Aetna Resources, LLC., a CVS Health company, is hiring for the following role in New York, NY: Sr. Decision Scientist to consult with internal clients to identify opportunities to develop and implement data science solutions to business problems by transforming data into meaningful information. Duties include: apply data mining, data modeling, machine learning, statistical analyses, and predictive and descriptive modeling to extract and manipulate data from multiple large data sources and inform solutions for data science teams; utilize data-oriented programming languages and visualization software to explore, analyze, and interpret large volumes of data and effectively communicate insights to inform business decisions; compare modeling techniques using statistical performance metrics and recommend improvements; structure data analysis to drive analytics insights and help data scientists determine the best analytical solutions; visualize, interpret, and report data findings to internal clients and leadership; collaborate with business partners to understand requirements and develop statistical analysis and predictive models to evaluate scenarios, predict outcomes, and provide usable information on health metrics and potential future outcomes; design and develop data science solutions using industry leading tools, technologies and best practices; mentor junior team members; and consult on the creation of analytics solutions that effectively weigh business strategy and technical tradeoffs relevant to big data environment. Telecommuting available. Multiple positions.

Requirements

Master’s degree (or foreign equivalent) in Computer Science, Data Science, Statistics, Mathematics, Analytics, Information Systems, or a related field and two (2) years of experience in the job offered or related occupation.
Analyzing large data sets from multiple data sources
Marketing analytics, clinical trials, or health research
Analytics experience within the healthcare, business, or retail sector
Machine learning, statistical analysis, and predictive modeling
Programming in R, SQL and Python
Visualization tools, including PowerBI or Tableau
Tools to automate CI/CD pipelines: Jenkins, GIT, or Control-M
“Big data” platforms including Hadoop (Azure, GCP, or AWS) and Spark, Airflow, Kafka, Hbase, Pig, or NoSQL
PySpark, Scala, or Java
Designing data models and solutions for analytical and reporting use cases
Machine Learning or NLP (Scikit-Learn, SpaCity, Pytorch, or Spark NLP)
Large-scale Spark, Data Warehouse, or Big Data implementation
Designing data architectures, including data pipelines, distributed computing engines, and machine learning infrastructure design

Responsibilities

Apply data mining, data modeling, machine learning, statistical analyses, and predictive and descriptive modeling to extract and manipulate data from multiple large data sources and inform solutions for data science teams
Utilize data-oriented programming languages and visualization software to explore, analyze, and interpret large volumes of data and effectively communicate insights to inform business decisions
Compare modeling techniques using statistical performance metrics and recommend improvements
Structure data analysis to drive analytics insights and help data scientists determine the best analytical solutions
Visualize, interpret, and report data findings to internal clients and leadership
Collaborate with business partners to understand requirements and develop statistical analysis and predictive models to evaluate scenarios, predict outcomes, and provide usable information on health metrics and potential future outcomes
Design and develop data science solutions using industry leading tools, technologies and best practices
Mentor junior team members
Consult on the creation of analytics solutions that effectively weigh business strategy and technical tradeoffs relevant to big data environment