Job Title: Data Science Manager / Head of Data Science (Team-Level)

About the Role

We are looking for a Data Science Manager to lead and grow a team of data scientists and ML engineers. You will be responsible for aligning the team’s output to strategic business goals, driving excellence in delivery, and nurturing team performance and development.

This role is best suited for a technically strong manager who also excels in project prioritization, team leadership, and stakeholder engagement.

Key Responsibilities

• Manage a team of data scientists, analysts, and/or ML engineers, providing direction, support, and mentorship
• Define and own the data science roadmap in alignment with business and product strategies
• Balance team workloads and prioritize initiatives based on impact, feasibility, and dependencies
• Oversee delivery of scalable, accurate, and interpretable ML models
• Provide guidance on technical architecture, experimentation, and reproducibility
• Conduct performance reviews, career development planning, and foster a collaborative team environment
• Serve as the main point of contact for cross-functional stakeholders, including product, engineering, and business leadership

Required Qualifications

Education:

• Bachelor’s degree in Data Science, Computer Science, Engineering, Mathematics, or related field
• Master’s or MBA is a plus

Experience:

• 8+ years of experience in data science or analytics, with at least 2–3 years in a leadership or management capacity
• Experience managing multi-disciplinary data teams and delivering technical outcomes tied to business results

Skills & Tools

• Strong technical knowledge of ML algorithms, statistics, and data pipelines
• Proven leadership and project management skills, with a track record of delivering cross-functional initiatives
• Ability to mentor team members in modeling, experimentation, and deployment best practices
• Skilled in stakeholder engagement, storytelling with data, and managing expectations
• Hands-on experience with tools such as Python, SQL, Git, MLflow, Spark, Tableau, and cloud platforms (AWS, GCP, Azure)
• Familiarity with agile methodologies, sprint planning, and metrics-driven team management

Preferred Qualifications:

• Background in organizational scaling (hiring, process design, career ladders, etc.)
• Experience driving ethical AI practices, bias audits, or governance frameworks
• Exposure to enterprise-wide data science applications or platform architecture