Data Science Manager - Machine Learning

As an experienced Data Science Manager, you will lead a team of data scientists and analysts to develop data-driven products, insights, and solutions. Your role will involve applying machine learning techniques, data strategy, and stakeholder management skills to address business challenges effectively. Key Responsibilities: - Lead, mentor, and develop a high-performing data science team. - Define and implement a data science roadmap aligned with business objectives. - Collaborate with Product, Engineering, and Business units to prioritize projects for maximum impact. - Supervise the design and deployment of predictive models, recommendation systems, and advanced analytics solutions. - Promote best practices in model development, feature engineering, validation, and monitoring. - Ensure data quality, reproducibility, and governance in all analytics initiatives. - Translate complex analytical findings into actionable business insights and recommendations. - Work with leadership to establish KPIs and evaluate the success of data-driven initiatives. - Promote a data-first culture within the organization. - Recruit, coach, and retain top talent in data science and analytics. - Conduct performance evaluations and set clear objectives for team members. - Encourage continuous learning, innovation, and collaboration within the team. Required Qualifications: - 8 - 14 years of experience, with a minimum of 3-5 years leading data science or analytics teams. - Strong knowledge of machine learning, statistics, and data modeling. - Hands-on experience with Python, R, SQL, and modern ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch). - Proven track record in managing projects end-to-end - from defining problems to deploying models. - Experience with large-scale datasets and cloud platforms (AWS, GCP, or Azure). - Excellent communication and stakeholder management abilities. Key Attributes: - Strategic thinker with practical technical skills. - Strong business acumen and problem-solving abilities. - Empathetic leadership style and a commitment to employee development. - Curious, data-driven, and dedicated to fostering innovation. As an experienced Data Science Manager, you will lead a team of data scientists and analysts to develop data-driven products, insights, and solutions. Your role will involve applying machine learning techniques, data strategy, and stakeholder management skills to address business challenges effectively. Key Responsibilities: - Lead, mentor, and develop a high-performing data science team. - Define and implement a data science roadmap aligned with business objectives. - Collaborate with Product, Engineering, and Business units to prioritize projects for maximum impact. - Supervise the design and deployment of predictive models, recommendation systems, and advanced analytics solutions. - Promote best practices in model development, feature engineering, validation, and monitoring. - Ensure data quality, reproducibility, and governance in all analytics initiatives. - Translate complex analytical findings into actionable business insights and recommendations. - Work with leadership to establish KPIs and evaluate the success of data-driven initiatives. - Promote a data-first culture within the organization. - Recruit, coach, and retain top talent in data science and analytics. - Conduct performance evaluations and set clear objectives for team members. - Encourage continuous learning, innovation, and collaboration within the team. Required Qualifications: - 8 - 14 years of experience, with a minimum of 3-5 years leading data science or analytics teams. - Strong knowledge of machine learning, statistics, and data modeling. - Hands-on experience with Python, R, SQL, and modern ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch). - Proven track record in managing projects end-to-end - from defining problems to deploying models. - Experience with large-scale datasets and cloud platforms (AWS, GCP, or Azure). - Excellent communication and stakeholder management abilities. Key Attributes: - Strategic thinker with practical technical skills. - Strong business acumen and problem-solving abilities. - Empathetic leadership style and a commitment to employee development. - Curious, data-driven, and dedicated to fostering innovation.