Data Science Manager - Machine Learning

Key Responsibilities :

- Lead, mentor, and grow a team of data scientists and analysts.

- Collaborate with business, product, and engineering teams to define project scopes and priorities.

- Translate complex business problems into measurable data science solutions.

- Own the roadmap for analytics, machine learning, and experimentation initiatives.

- Design, build, and deploy ML/statistical models (classification, NLP, forecasting, clustering, etc.).

- Oversee the full data science lifecycle: problem scoping data exploration modeling evaluation deployment.

- Ensure model performance, scalability, and continuous improvement.

- Work with data engineering teams to improve data pipelines, data quality, and automation.

- Build dashboards, reports, and data products to support decision-making.

- Present insights, model results, and recommendations to senior stakeholders.

- Communicate technical concepts in a clear, business-friendly manner.

- Manage project timelines, stakeholder expectations, and cross-functional alignment.

Required Skills & Experience :

- 4- 8 years of industry experience in Data Science, Analytics, or ML Engineering. 2+ years of experience leading teams (formal or informal).

- Strong programming skills in Python/R, experience with ML libraries (scikit-learn, TensorFlow, PyTorch).

- Solid statistical foundation and expertise in ML algorithms.

- Proficiency in SQL and working with large datasets.

- Experience with MLOps tools (MLflow, Airflow, Docker, etc.) is a plus.

- Strong business problem-solving skills and ability to drive measurable impact.

- Experience in A/B testing, experimentation, or causal inference (added advantage).

Nice-to-Have :

- Experience in product-based or high-growth tech environments.

- Exposure to cloud platforms (AWS, GCP, Azure) and modern data warehouses (Snowflake, BigQuery, Redshift).

- Experience building and deploying scalable ML solutions in production.