Senior Data Science Manager

Job Summary

We are seeking an experienced and strategic Data Science Manager to lead a team of data scientists and machine learning engineers in developing scalable AI/ML solutions. The ideal candidate will drive data-driven decision-making, manage end-to-end analytics projects, and collaborate with cross-functional teams to solve complex business problems using advanced statistical and machine learning techniques.

Key Responsibilities

• Lead and mentor a team of Data Scientists, ML Engineers, and Analysts.
• Design and implement machine learning models, predictive analytics solutions, and AI-driven products.
• Define data science strategy aligned with business objectives.
• Collaborate with Product, Engineering, Business, and Leadership teams to identify data-driven opportunities.
• Oversee model development lifecycle including data collection, feature engineering, training, validation, deployment, and monitoring.
• Drive experimentation, A/B testing, forecasting, recommendation systems, and optimization initiatives.
• Ensure scalability, reliability, and performance of ML models in production environments.
• Present analytical insights and recommendations to senior stakeholders and executive leadership.
• Establish best practices for data governance, model validation, and MLOps processes.
• Stay updated with the latest advancements in AI, Generative AI, Deep Learning, and data technologies.

Required Skills

• Strong expertise in Machine Learning, Statistical Modeling, and Predictive Analytics.
• Proficiency in Python, R, SQL, and data science libraries/frameworks.
• Experience with Deep Learning frameworks such as TensorFlow or PyTorch.
• Knowledge of NLP, Computer Vision, Time Series Forecasting, or Recommendation Systems.
• Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
• Experience in big data technologies like Spark, Hadoop, or Databricks.
• Strong understanding of MLOps, CI/CD pipelines, and model deployment strategies.
• Excellent stakeholder management, leadership, and communication skills.
• Strong business acumen and problem-solving abilities.

Preferred Qualifications

• Bachelors or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
• PhD is a plus.
• Experience leading enterprise-level AI/ML initiatives.
• Exposure to Generative AI, LLMs, and AI governance frameworks preferred.

Tools & Technologies

• Python, R, SQL
• TensorFlow, PyTorch, Scikit-learn
• Spark, Hadoop, Databricks
• AWS / Azure / GCP
• Tableau / Power BI
• Docker, Kubernetes
• Git, MLflow, Airflow

Nice to Have

• Experience in FinTech, Healthcare, Retail, or Product-based organizations.
• Knowledge of Responsible AI and ethical AI practices.
• Experience managing globally distributed teams.