Job Title

Role SummaryWe are looking for a technically strong and visionary Data Science Manager / Senior Manager to lead a team of data scientists and ML engineers in building scalable, production-grade AI solutions. This role demands deep expertise in machine learning, hands-on technical leadership, and the ability to architect and guide complex data science initiatives from ideation to deployment.Key ResponsibilitiesTechnical Leadership- Architect and oversee the development of advanced ML models including supervised, unsupervised, and deep learning approaches. - Drive best practices in model development, validation, deployment, and monitoring. - Lead code reviews, model audits, and ensure reproducibility and scalability of solutions. - Champion ML Ops practices and CI/CD pipelines for ML workflows.Team Management- Mentor and grow a team of data scientists and ML engineers. - Foster a culture of technical excellence, ownership, and continuous learning. - Set clear goals, provide feedback, and support career development.Strategic Execution- Translate business problems into data science solutions with measurable impact. - Prioritize projects based on ROI, feasibility, and strategic alignment. - Collaborate with cross-functional teams including engineering, product, and domain experts.Innovation & Thought Leadership- Stay ahead of the curve on emerging ML techniques, tools, and frameworks. - Evaluate and integrate cutting-edge technologies into the team’s workflow. - Represent the data science function in technical forums and leadership discussions.Required Qualifications- Expertise in Computer Science, Machine Learning, Statistics, or related field. Min Graduate - 8+ years of experience in data science, with 3+ years in a technical leadership role. - Proven track record of deploying ML models in production environments. - Strong programming skills in Python (preferred), R, or Scala. - Deep understanding of ML frameworks (e.g., PyTorch, TensorFlow, XGBoost, scikit-learn). - Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes). - Familiarity with MLOps tools (MLflow, Airflow, SageMaker, etc.).Education: Preferably From Mathematics and Statistics backgroundLocation: HyderabadWork mode: HybridShift time: 2 PM to 11 PMThanks & Regards,Shaik.ahamed@