[ref. g40751222] Director of Data Science

Job Description

Overview

This role requires a unique blend of technical depth, strategic thinking, and leadership excellence.

1. Growth-Focused Data Science

• Lead the design and execution of a data science roadmap aligned with growth goals.
• Develop data products and analytical models to improve marketing efficiency, reduce churn, and optimize revenue streams.
• Translate business questions into scalable experiments and data initiatives.

1. Strategic & Visionary Leadership

• Define a long-term vision for data sciences role in business growth.
• Stay ahead of emerging technologies and integrate them into team capabilities.
• Align team objectives with company-wide strategic goals.

1. Cross-Functional Influence

• Act as a thought partner to senior leadership across product, marketing, engineering, and strategy.
• Communicate insights clearly to influence high-level decisions.
• Represent the function externally with partners, vendors, and at industry events.

1. Team & Resource Management

• Build and lead a high-performing team of data scientists, analysts, and engineers.
• Manage budgets, resource allocation, and project prioritization based on business impact.
• Provide mentorship and coaching to emerging leaders within the team.

1. Organizational Change & Enablement

• Lead change management initiatives involving new tools, processes, and structures.
• Communicate change with clarity and empathy, ensuring team buy-in.
• Build frameworks that allow the team to adapt and thrive in evolving environments.

What Youll Need

• 8-10 + years in data science, including leadership of multi-disciplinary teams.
• Proven track record of delivering measurable business impact through analytics.
• Experience managing managers and scaling data organizations.

• Masters or Ph.D. in Computer Science, Data Science, Statistics, or a related field.

• Deep knowledge of statistics, machine learning, experimentation, and causal inference.
• Experience designing and deploying analytical models in production environments.
• Ability to lead complex data initiatives from design through implementation.

• Strong understanding of commercial strategy, customer behavior, and growth levers.
• Ability to connect data initiatives to business value e.g., revenue, retention, cost efficiency.
• Strategic thinker with a focus on long-term value creation.

• Confident communicator who can simplify complex topics for diverse audiences.
• Able to inspire, influence, and drive alignment across senior stakeholders.
• Comfortable navigating ambiguity and making high-impact decisions.