below marketmost similar roles pay hereabove market
This role pays less than
65%
of similar roles. Most pay
$162,000–$228,950
— the blue band above.
At the midpoint, this role pays about
$167k
versus about
$195k
for comparable roles.
Based on 240 similar postings.
Employer
About CVS Health
CVS Health is a leading American healthcare company operating retail pharmacies, pharmacy benefit management services, and a health insurance segment through Aetna, one of the nation''s largest health insurers. Industry: Healthcare & Pharmacy
CVS Health currently has
124 open roles
on FindRole.
Listed pay typically runs
$108,922–$260,590
across 120 roles with salary data.
The Senior Data Scientist - Risk Prediction Engine joins a team of healthcare data scientists to develop next-generation risk prediction models. This role involves leveraging analytical and machine learning skills to provide insights and model solutions for stakeholders across the CVS Health and Aetna organizations. You will develop algorithms and statistical predictive models to evaluate scenarios, perform analyses on structured and unstructured data, and collaborate with business partners to develop performance metrics. The work requires utilizing petabytes of data and industry knowledge of actuarial partners to solve complex business problems. Key technologies include SQL, Python, R, Spark, and Cloud computing platforms like AWS, GCP, and MS Azure. Candidates must also demonstrate hands-on experience with large language models and AI tools to drive efficiency and innovation.
What does a Data Scientist earn in New York?
Median $173200 from 47 postings across 18 companies.
Develop and use algorithms and statistical predictive models to evaluate scenarios and future outcomes.
Perform analyses of structured and unstructured data to solve complex business problems using advanced statistical techniques.
Develop predictive models, statistical analyses, and performance metrics to meet specific business goals.
Create and deliver presentations to stakeholders regarding analytics results and proposed solutions.
Use SQL, Python, Spark, and Cloud computing to explore and interpret large volumes of data.
Incorporate large language models and AI tools into data science processes to drive efficiency and innovation.
Formulate hypotheses and test new methods quickly to identify promising analytical approaches.
Apply risk management judgment when validating models that inform business-critical decisions.
What we're looking for
Bachelor's degree in Mathematics, Statistics, Computer Science, Business Analytics, Economics, Physics, Engineering, or a related discipline.
Master's or PhD degree in Mathematics, Statistics, Computer Science, Business Analytics, Economics, Physics, Engineering, or a related discipline (preferred).
3+ years of professional experience in data analytics, BI, data engineering, or applied data science.
5+ years of professional experience in data analytics, BI, data engineering, or applied data science (preferred).
3+ years of experience with SQL and Python/R.
5+ years of experience with SQL and Python/R (preferred).
Extensive experience with SQL, Python, Spark, and Cloud computing (AWS, GCP, MS Azure).
Hands-on experience leveraging large language models and AI/ML ecosystem tools to deliver impactful products.
Python
Scala
R
PyTorch
Hugging Face
LangChain
Vector Databases
LLMOps
AWS
Machine Learning
Deep Learning
Statistics
Time Series
Sentiment Analysis
Clustering
Classification
Python
AWS
Spark
H2O
SQL
Scala
R
Machine Learning
NLP
Generative AI
Conda
Deep Learning
Time Series
Clustering
Classification
Sentiment Analysis
Statistical Modeling
Big Data
Python
R
Scala
Machine Learning
Generative AI
Spark
NoSQL
ETL
Data Warehousing
Statistical Modeling
GLM
Logistic Regression
Decision Trees
Time-series Forecasting
Autoencoders
GANs
Graph Data