Job description
**Candidate can sit in Boston, MA with partial travel to CVS Woonsocket, RI office **
Please note: Only candidates with relevant, current Machine Learning/AI Data Science hand’s on, in-the-field experience – 2+ years will be considered/ Academia experience is not part of in-the-field work.
CVS health is seeking an exceptional Artificial Intelligence – Machine Learning Scientist to the join its Loyalty & Personalization team. This role will have the unique opportunity to build, implement, and upkeep a Personalization Engine product serving over 70M loyalty program customers. In this role, you will apply a rigorous machine learning approaches to build and enhance the capabilities of the product. As a member of the team you will have a deep knowledge base in Machine Learning and in- depth expertise in applying automated solutions in Decision Optimization/Workflow processes.
**Only applicants that meet the requirements listed below will be considered**
REQUIRED EXPERIENCE/MUST HAVE:
- At least 2 years work experience – Computer Science, Programming skills
- At least 2 years work experience – Probability and Statistics
- At least 2 years work experience – Data Modeling and Evaluation
- At least 1-2 years work experience – Experience with Big Data and Machine Learning in cloud environment (Azure/Databricks experience strongly)
- At least 2 years work experience – Expert programming skills in at least two of the following: Python, R, Scala, Spark or Java. Strong preference for Python/Spark/Keras
- At least 1-2 years work experience – in applying supervised, unsupervised and semi-supervised learning techniques
- At least 1-2 years work experience – Building Machine Learning pipeline ( data ingestion, feature engineering, modeling including ensemble methods, predicting, explaining, deploying and diagnosing over fitting )
- At least 2 years work experience – in model selection and sampling
- some experience – deep learning and neural nets (strong preference for experience with Keras)
- Preference for some experience with Natural Language Processing (NLP)
- Candidates with experience in retail or loyalty programs preferred
Position Summary:
The Machine Learning Scientist will be expected to thrive and have demonstrate success in an environment which offers complex problems, big challenges, and quick changes. They will deliver model and solution artifacts (e.g. operational code to support system decision/workflow and technical documentation) while operating autonomously in a product development setting to meet release schedules. They will be expected to balance detailed execution goals with speed and business constraints. Solid collaborative skills, ability to abstract complex problem into machine learning solutions, an appreciation for learning, and extreme attention to detail are necessities. The successful candidate will be a recognized expert for their technical and critical thinking abilities.
Role Responsibilities:
- Provide technical expertise in building and maintaining artificial intelligence product in cloud environment
- Building scalable solutions as part of artificial intelligence pipeline
- Collaborate with IT/Engineering to ensure proposed solutions are implemented/supported
- Ensure implemented solutions within production meet design requirement
- Create Machine Learning pipelines and train models
- Work in code notebooks
- Build & validate models
- Monitor & retrain models
- Monitor and bug fix solutions
- Use code repositories to version and share code/notebooks
- Analyze product performance to find opportunities and propose solutions for enhancement, improvement, and efficiency
- Conduct analyses and build solutions as needed to supplement pipeline orchestration and execution
Education:
- Master’s in Data Science, Computer Science or other relevant, related fields
#LI-SLT1
Seniority Level
Executive
Industry
- Hospital & Health Care
Employment Type
Full-time
Job Functions
- Analyst
- Information Technology
- Marketing
More Information
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1