Machine Learning Engineer

CVS Health•Irving, TX

4d•$96,034 - $144,200•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. Aetna Resources, LLC., a CVS Health company, is hiring for the following role in Irving, TX: Machine Learning Engineer to build, deploy, and monitor artificial intelligence (AI)/machine learning (ML) models to automate processes and transform data into meaningful information.

Requirements

Master’s degree (or foreign equivalent) in Computer Science, Engineering, Machine Learning, Statistics, Mathematics, Analytics, Information Technology, or a related field and two (2) years of experience in the job offered or related occupation.
Two (2) years of experience in CI/CD, Jenkins, GIT, or DevOps.
Two (2) years of experience in Java, Python, or Node.js.
Two (2) years of experience in JavaScript.
Two (2) years of experience in Agile methodologies or SAFe Software Development Principles.
Two (2) years of experience in REST, SOAP or Webservice APIs.
Two (2) years of experience in MySQL.
Two (2) years of experience in SAS or SQL programming.
Two (2) years of experience in Software development life cycle (SDLC) and best practices.
Two (2) years of experience in Software testing, quality assurance, and troubleshooting.
Two (2) years of experience in Writing application code and deploying to production.
Two (2) years of experience in Relational database concepts.

Responsibilities

Apply data modeling, machine learning, predictive modeling, and statistical analysis to extract and analyze information and build end-to-end solutions to meet organizational objectives.
Research, experiment with, implement, train, and re-train ML algorithms and tools.
Engage with business stakeholders to translate requirements into technical solutions leveraging ML models and technologies.
Analyze data and identify differences in data distribution that could impact model performance in real-world use cases using industry leading tools, technologies and best practices.
Design ML approach, apply appropriate techniques, and develop custom algorithms as needed to address business problems and predict outcomes of interest.
Apply sampling techniques and investigate adversarial trends, identify behavior patterns, and respond with logic changes.
Compare models using statistical performance metrics and ensure accuracy of business metrics.
Visualize, interpret, and report data findings to internal clients and leadership.
Collaborate with Data Engineers, Data Scientists, and Product Managers to drive towards business objectives and key performance indicators (KPIs).