Manager - Data Science & ML Engineering

Role & responsibilities

Zelis is seeking a hands-on Manager Data Science & ML Engineering to lead the development and productionization of AI/ML solutions. This role is responsible for managing a team of data scientists and ML engineers, and driving the end-to-end lifecycle of machine learning solutions—from problem definition and data analysis to model deployment, monitoring, and continuous improvement.

The ideal candidate combines strong expertise in machine learning and advanced analytics with experience in building scalable, production-grade ML systems (MLOps). You will partner closely with business, data engineering, and technology teams to deliver impactful, data-driven solutions that drive measurable business outcomes.

Key Responsibilities

• Lead, mentor, and manage a team of Data Scientists and ML Engineers (MLOps).
• Own end-to-end delivery of AI/ML solutions: problem framing, data preparation, model development, deployment, and monitoring.
• Design and oversee development of machine learning models (regression, classification, clustering, anomaly detection, NLP/LLMs).
• Build and scale ML pipelines, CI/CD processes, and automated retraining and monitoring frameworks.
• Ensure models are production-ready, scalable, and aligned with best practices in model governance and reproducibility.
• Partner with business stakeholders to translate requirements into data-driven solutions and measurable outcomes.
• Collaborate with data engineering and platform teams to build robust data pipelines and ML infrastructure.
• Track model performance, business impact, and ROI; drive continuous improvement.
• Communicate complex analytical insights and system designs to both technical and non-technical audiences.
• Manage multiple priorities in a fast-paced environment and proactively address risks and dependencies.

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.
• 8–12+ years of experience in Data Science, Machine Learning, or related fields.
• 2–4+ years of experience in team leadership or people management.
• Strong hands-on expertise in machine learning, statistical modeling, and data analysis.
• Experience in building and deploying production-grade ML systems (MLOps).
• Proficiency in Python and SQL; experience with NLP/LLMs is a plus.
• Experience with cloud platforms (AWS or Azure) and tools such as SageMaker, Databricks, Snowflake, or PySpark.
• Solid understanding of ML lifecycle, CI/CD, model monitoring, and governance practices.
• Strong communication, problem-solving, and stakeholder management skills.

Preferred Qualifications

• Experience working with healthcare or insurance data.
• Familiarity with modern AI/GenAI use cases and frameworks.
• Experience with collaboration tools such as GitHub, GitLab, and Jupyter notebooks.

Additional Information

• This is a hands-on leadership role requiring both technical depth and delivery ownership.
• Opportunity to work on modern AI/ML and GenAI initiatives with high business impact.