Manager - Data Science & ML Engineering
Posted Apr 16, 2026
Key Responsibilities:
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Lead, mentor, and manage a team of Data Scientists and ML Engineers (MLOps). - Take charge of end-to-end delivery of AI/ML solutions, including problem framing, data preparation, model development, deployment, and monitoring. - Design and supervise the development of machine learning models encompassing regression, classification, clustering, anomaly detection, and NLP/LLMs. - Construct and expand ML pipelines, CI/CD processes, and automated retraining and monitoring frameworks. - Ensure that models are production-ready, scalable, and comply with best practices in model governance and reproducibility. - Collaborate with business stakeholders to convert requirements into data-driven solutions and measurable outcomes. - Work closely with data engineering and platform teams to construct robust data pipelines and ML infrastructure. - Monitor model performance, business impact, and ROI, and drive continuous improvement. - Effectively 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. Qualification Required:
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Bachelors or Masters degree in Data Science, Statistics, Computer Science, or a related field. - 812+ years of experience in Data Science, Machine Learning, or related fields. - 24+ 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. Role Overview: Zelis is looking for a hands-on Manager Data Science & ML Engineering to spearhead the development and operationalization of AI/ML solutions. As the manager, you will be responsible for overseeing a team of data scientists and ML engineers, leading the entire lifecycle of machine learning solutions from problem identification and data analysis to model deployment, monitoring, and continuous enhancement. This is a pivotal leadership role with the opportunity to work on cutting-edge AI use cases and influence AI/ML delivery practices and model governance within the organization. Key Responsibilities: