Data Science Manager

Join Our Team: Do Meaningful Work and Improve People’s Lives 

Our purpose, to improve customers’ lives by making healthcare work better, is far from ordinary. And so are our employees. Working at Premera means you have the opportunity to drive real change by transforming healthcare. 

To better serve our customers, we’re creating a culture that promotes employee growth, collaborative innovation, and inspired leadership. We are committed to creating an environment where employees can do their best work and where best-in-class talent comes, stays, and thrives! As a result of these efforts we are proud to share that Forbes ranked Premera among America’s 2023 Best Midsize Employers and America's 2023 Best Employers By State.

Learn how Premera supports our members, customers and the communities that we serve through our Healthsource blog:  https://healthsource.premera.com.

As a Data Science Manager, you will develop and lead a team of scientists and AI engineers dedicated to revolutionizing healthcare through cutting-edge AI and ML solutions. This management role focuses on hands-on ideation, development, deployment, and monitoring of AI/ML solutions.

This is a virtual/telecommuter position, working from home.

What you’ll do:

• Develop a high-performing team of scientists and engineers, fostering a culture of excellence and collaboration.

• Collaborate with cross-functional teams to ideate and develop innovative AI/ML solutions addressing complex healthcare challenges.

• Lead hands-on AI/ML development efforts, ensuring timely delivery of scalable, high-quality products.

• Ensure, along with the team, the monitoring of all production products’ ongoing fitness for use.

• Partner with the team to routinely assess the business value realized by ML/AI solutions.

• Implement and ensure adherence to SDLC, peer review, and responsible AI best practices, including ethical considerations like fairness and explainability.

• Mentor individual team members to achieve their full potential as scientists and engineers.

• Foster within the team principled, agile-like development practices.

• Apply team-wide documentation practices that will enhance maintainability and ensure adherence to CD&A and corporate policies and expectations.

• Present impact of solutions to business leaders and other non-technical stakeholders in a clear, concise, and compelling manner.

What you’ll bring:

Required Qualifications

• Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related field or 2+ years of experience in a related, professional IT/analytics position.

• 2+ years leading highly technical/analytical teams through their work.

• 5+ years of industry experience in developing, deploying, and maintaining AI / ML systems.

• 5+ years of experience conducting quantitative analytics.

Preferred Qualifications

• Master’s Degree/PhD in a quantitative, computational, or scientific field.

• 2+ years as a manager of highly technical/analytical people and teams.

• 5+ years working within Agile-like teams and environments.

• 5+ years of healthcare and healthcare data knowledge.

Knowledge, Skills, and Abilities

• Proven experience developing and optimizing ML solutions using languages like Python and libraries such as NumPy, Pandas, Matplotlib and scikit-learn.

• Experience in developing deep learning models (CNNs, transformers, LSTMs, etc.) with frameworks such as TensorFlow, PyTorch, and Keras.

• Proven experience at debugging ML/AI systems and enhancing predictive performance as well as operational performance.

• Proven experience working with ML lifecycles.

• Prior exposure to software design patterns, microservices, distributed computing, container orchestration, and other relevant architectures.

• Knowledge of and experience in implementing ethical AI practices (i.e.:  explainable AI, fairness, and bias mitigation).

• Solid SQL programming skills.

• Proven experience with a variety of statistical analyses such as hypothesis testing, experimental design, regression analysis, clustering, time series analysis, anomaly detection and sequence analysis.

• Prior experiences developing