Data Scientist Manager

Manager, Data Science Machine Learning & MLOps

Location: Pune
Employment Type: Permanent
Work Model: Work From Office 5 Days
Positions: 1
Shift: 9:00 AM–6:00 PM / 2:00 PM–11:00 PM IST

About the Role

We are looking for a Manager, Data Science with a strong technical and hands-on background in Data Science, Machine Learning, MLOps and scalable ML solution architecture.

The role will lead ML initiatives from conceptualization through deployment and monitoring, while providing technical direction, mentoring Data Scientists/ML Engineers, and driving engineering best practices across the ML lifecycle.

The ideal candidate will bring strong experience in Healthcare, along with exposure to regulated environments, DevSecOps, CI/CD and production-grade ML solutions.

Key Responsibilities

• Lead Machine Learning projects from conceptualization through development, deployment, monitoring and continuous improvement.
• Define and implement ML engineering best practices, standards and scalable solution architectures.
• Design and implement production-grade ML solutions across cloud and on-premise environments.
• Drive adoption of MLOps principles across the complete ML lifecycle.
• Lead, mentor and develop Data Scientists and ML Engineers, fostering technical excellence and continuous improvement.
• Manage and coordinate teams of significant size, preferably 15–20 members.
• Partner with Product, Engineering, Architecture and Business teams to translate business objectives into ML and analytics solutions.
• Conduct technical reviews, identify complex engineering issues and drive effective solutions.
• Ensure ML solutions meet requirements for performance, scalability, reliability, security and maintainability.
• Drive ML automation, CI/CD and DevSecOps practices across development and deployment workflows.
• Stay current with emerging AI/ML technologies, methodologies and industry practices.
• Support advanced analytics initiatives and identify opportunities for innovation and intellectual property development.
• Ensure effective communication and collaboration across technical, business and cross-functional teams.
• Apply appropriate governance and regulatory practices within ML engineering and deployment environments.

Must-Have Skills & Experience

• 15+ years of overall experience in Data Architecture, Software Engineering, Analytics and/or Data Science.
• Minimum 3 years of experience leading Data Science / Machine Learning teams.
• Minimum 3 years of hands-on AI/ML experience.
• Minimum 2 years of Healthcare domain experience.
• Minimum 3 years of experience with regulatory environments, DevSecOps and CI/CD pipelines.
• Strong understanding of Machine Learning algorithms and principles.
• Expert-level Python skills.
• Experience with ML frameworks such as Scikit-learn, TensorFlow, Keras or PyTorch.
• Experience designing and deploying scalable, production-grade ML solutions.
• Strong understanding and implementation of MLOps principles from development through monitoring.
• Experience with Azure, particularly Azure ML and Databricks.
• Experience with ML automation platforms/tools such as MLflow and/or Kubeflow.
• Strong understanding of DevSecOps, CI/CD and Infrastructure as Code.
• Experience with tools such as GitHub/GitLab, Docker and Kubernetes.
• Strong software design and development lifecycle knowledge.
• Strong experience with RDBMS / NoSQL databases, preferably MongoDB.
• Experience with Flask-based applications and UI/UX-enabled solutions is preferred.
• Strong communication, stakeholder management and team leadership skills.
• Experience working in Agile environments.

Leadership Expectations

• Lead and mentor a high-performing team of Data Scientists and ML Engineers.
• Build a culture of technical excellence, innovation and continuous learning.
• Provide technical mentorship and career development guidance.
• Drive collaboration between Data Science, Engineering, Product, Architecture and Business teams.
• Take ownership of ML project strategy, execution, technical quality and delivery outcomes.
• Champion modern ML engineering and MLOps practices across the organization.

Education

Any full-time Graduate degree.

A Master's degree in Computer Science, Engineering, Statistics, Mathematics, Physics or another quantitative discipline is preferred.

Preferred Experience

• Healthcare / Life Sciences domain experience.
• Experience working in highly regulated environments.
• Regulatory compliance and audit experience.
• Experience managing teams of 15–20 Data Scientists / ML Engineers / Analysts.
• Experience with advanced analytics, Generative AI or emerging AI/ML technologies.

Compensation & Benefits

• CTC: Includes 10% variable.
• Medical insurance coverage up to 10 Lakhs for employee, spouse, children and two parents.
• Additional coverage for in-laws available at an additional cost.
• Shift allowance:
• Morning/Afternoon: 400
• Night: 1,500/month (subject to confirmation)
• Internet reimbursement.
• Work-from-home office setup reimbursement up to 15,000.
• Free employee transportation – pickup and drop.
• Relocation benefits available.

Interview Process

1. Recruiter / Floacareer Interview
2. Client Interview – 3 Rounds
• Technical
• Techno-Managerial
• Cultural Fitment
3. HR Round