Senior Machine Learning Engineer

We are a healthcare technology and health insurance provider offering a wide range of services. We’re committed to better health and better health care − in our communities and beyond. We serve more than 4 million members and we employ over 5k people across the country who are passionate about making health care better for all.

Health care is changing, and we're leading the way. Our employees bring energy and creativity to the workplace, and it shows in our innovative approach to improving the health and well-being of our communities.

We are looking for a Senior Machine Learning Engineer to work closely with data scientists and other stakeholders to design and maintain advanced data models and data pipeline processes and machine learning pipelines. You'll be responsible for developing and supporting advanced and complex workflows for internal and external clients. You will design and grow a data and AI/ML infrastructure that powers our ability to make timely and data-driven decisions. This role will be key in our move to AWS SageMaker and advancing our engineering capabilities. We plan to migrate all ML models (new and legacy) into the platform and our ML Engineers will work closely with all Data Scientist to ensure these models are transitioned and supported as intended.

Job Duties:

• Define and extract data from multiple sources, integrate disparate data into a common data model, and integrate data into a target database, application, or file using efficient programming processes
• Document, and test complex data systems that bring together data from disparate sources, making it available to data scientists, and other users using scripting and/or programming languages
• Improve, deploy, and maintain models prepared by Data Scientists into production-grade cloud systems using scalable, efficient machine learning operations pipelines
• Write and refine code to ensure performance and reliability of data extraction and processing
• Lead requirements gathering sessions with business and technical staff to distill technical requirement from business requests
• Develop advanced SQL queries to extract data for analysis and model construction
• Own delivery of large, complex data and ML engineering projects
• Design and develop scalable, efficient data pipeline processes to handle data ingestion, cleansing, transformation, integration, and validation required to provide access to prepared data sets to analysts and data scientists

Ideal Background:

• 7+ years of experience with Oracle, Data Warehouses and Data Lakes, Big Data platforms and programming in Python, R or other related language.
• Understanding of ML Algorithms, experience creating & executing efficient MLOps pipelines, and tuning ML models
• Experience with Python analytics packages such as scikit-learn, NumPy, Pandas etc.
• Exposure to clinical, healthcare, or insurance data
• Experience working in AWS and/or using Linux based systems
• Experience working with Amazon SageMaker
• Expert in the deployment of ML models on big data platforms
• Demonstrated experience performing data validation on prepared data sets
• Bachelor’s degree in Computer Science