Machine Learning Engineer - RCS Analytics (ML, Experimentation)

At CVS Health, we’re building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care.

As the nation’s leading health solutions company, we reach millions of Americans through our local presence, digital channels and more than 300,000 purpose-driven colleagues – caring for people where, when and how they choose in a way that is uniquely more connected, more convenient and more compassionate. And we do it all with heart, each and every day.

Position Summary

Rich Communication Services (RCS) is revolutionizing customer interactions by enhancing traditional SMS/MMS communications. We are committed to deploying sophisticated customer journeys and audience designs, leveraging predictive analytics. We are seeking a Machine Learning Engineer with a strong focus on experimentation to join our team. This role involves developing models for audience design, designing and executing A/B experiments, and performing statistical analyses. They will be expected to onboard to new tools for executing RCS tactics and share their learnings back to the team to empower the team’s growth. The ideal candidate will work closely with data engineering and MLOps to ensure scalable and sustainable solutions.

The Machine Learning Engineer – RCS Analytics will work with data related to a wide range of customer interactions and analytics. This role is responsible for the deployment of large-scale systems, experimentation, and predictive model design, working closely with data engineering and MLOps. Continuous learning and improvement in both business subject matter expertise and emerging algorithms and techniques will be a key focus. In this role, you will establish best practices, create workflow efficiencies, elevate coding standards, and work with model training and MLOps for the team.

Key Responsibilities

• Build and facilitate statistical and machine learning solutions across large-scale systems and campaigns, ensuring deployment and updates in collaboration with data engineering.

• Develop and participate in presentations and consultations to existing and prospective stakeholders on analytics results and solutions.

• Collaborate with internal and external peers and managers to exchange complex information related to areas of specialization.

Location: Hybrid schedule in New York City office.

Required Qualifications

• 2+ years of experience with data preprocessing, feature engineering, and model evaluation techniques, with previous experimentation experience executing and measuring A/B tests

• 2+ years of experience in building end-to-end machine learning models and data-intensive systems in production

• 2+ years of strong background in Data Science with a focus on software development best practices

• 2+ years of proficiency in Python, SQL, and MLOps and experience working with and/or developing APIs

• 2+ years of experience in cloud environments

Preferred Qualifications

• Demonstrated ability to design and build distributed data-intensive products including Front End and web app development

• Experience with Snowflake or GCP is a major plus.

• Familiarity with Generative AI and agentic design

• Proficiency in mathematical analysis methods, machine learning, statistical analyses, and predictive modeling, with in-depth specialization in certain areas.

• Experience in causal impact analysis from scaled experimentation

Education

• Bachelor's degree or equivalent work experience in Mathematics, Statistics, Computer Science, Business Analytics, Economics, Physics, Engineering, or related discipline.

• Master's degree preferred.

Anticipated Weekly Hours

40

Time Type

Full time

Pay Range

The typical pay range for this role is:

$86,520.00 - $173,040.00

This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls.  The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors.  This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. 
 

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