This role is responsible for leading the data science function to solve complex business problems using advanced analytics and Machine Learning. The manager acts as a bridge between technical data teams and business stakeholders, ensuring that data strategies align with organizational goals. This position carries accountability for the end-to-end lifecycle of data science projects, from ideation and model development to deployment and monitoring, while fostering a culture of technical excellence and innovation.
Leadership & Team Management:
- Recruit, mentor, and coach a team of Data Scientists and Analysts to build strong in-house capability.
- Conduct performance reviews, manage career development paths, and foster a collaborative and high-performance team culture.
- Define resource allocation and prioritize the data science roadmap based on business impact.
Technical Strategy & Execution:
- Define and oversee the end-to-end Machine Learning (ML) lifecycle, including data collection, feature engineering, model training, validation, and deployment (MLOps).
- Translate high-level business problems into actionable data science requirements and technical solutions.
- Oversee the design and implementation of scalable ETL flows and data pipelines to support complex modeling.
- Ensure data quality, governance, and ethical standards (e.g., bias mitigation in algorithms) are maintained across all projects.
Stakeholder Management & Business Impact:
- Act as the primary liaison between the data team and business owners/product managers to uncover insights and define success metrics (KPIs).
- Present complex technical findings and model performance to non-technical stakeholders in clear, actionable language.
- Identify opportunities for process improvements and cost savings through automation and advanced analytics.
- Plan and participate in the organization's broader technology roadmap to ensure data capabilities keep pace with business needs.
Experience & Education:
- Master's in Statistics, Mathematics, Computer Science, or a related quantitative field (preferred); Bachelor's required.
- 7+ years of relevant experience in data science, data analytics, or related fields, with at least 3 years in management or lead capacity.
- Proven track record of leading and delivering real-world Machine Learning projects that resulted in positive business outcomes (ROI).
Technical Expertise:
- Deep understanding of statistical analysis, predictive modeling, clustering, classification, and regression techniques.
- Strong command of programming languages (Python, R) and database languages (SQL).
- Familiarity with cloud platforms (AWS, Azure, or GCP) and data engineering tools (ETL, data warehousing).
- Knowledge of visualization tools (Power BI, Tableau) to create executive-level dashboards.
Soft Skills:
- Excellent communication and presentation skills with the ability to influence senior leadership.
- Strategic thinker with strong business acumen; able to prioritize projects that drive maximum value.
- Goal-driven, highly motivated, with a desire to take the lead and learn new skills.
- Ability to handle multiple complex projects concurrently, balance competing priorities, and meet strict deadlines.
- High integrity and work ethic; ability to employ patience and empathy while dealing with conflict or differing viewpoints within the team.
