Job Description
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 Masters 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
(ref:hirist.tech)
