Data Science Lead

About the Role
We are seeking an experienced Data Science Lead to define and advance the organization's machine learning, artificial intelligence, and decision intelligence capabilities. This role will lead a team of Data Scientists and partner with cross-functional stakeholders to develop scalable analytics and AI solutions that enhance customer experiences, optimize business performance, and unlock new growth opportunities.
The ideal candidate combines deep technical expertise with strong leadership skills, bringing a track record of translating complex business challenges into impactful data products. You will play a key role in shaping the data science roadmap, establishing best practices, and building a high-performing team that delivers measurable outcomes through advanced analytics and machine learning.
Key responsibilities
Lead AI and Machine Learning Initiatives
Drive the development, deployment, and continuous improvement of machine learning, predictive analytics, and AI solutions that support strategic business objectives.
Identify high-impact opportunities where data science can improve decision-making, automation, operational efficiency, and customer outcomes.
Translate Business Challenges into Scalable Solutions
Partner with senior leaders and cross-functional teams to understand business needs and define data-driven strategies.
Develop roadmaps that align technical initiatives with organizational goals and measurable business results.
Build Advanced Customer and Behavioral Intelligence Capabilities
Oversee initiatives involving customer segmentation, behavioral modeling, recommendation engines, propensity analysis, forecasting, predictive scoring, and optimization frameworks.
Leverage advanced analytical techniques to uncover actionable insights and drive more personalized experiences.
Drive Model Excellence and Operationalization
Establish best practices across model design, validation, experimentation, monitoring, explainability, and governance.
Ensure machine learning solutions are scalable, reliable, and production-ready through close collaboration with engineering and platform teams.
Foster a Data-Driven Culture
Promote evidence-based decision-making by integrating data science insights into business processes and strategic planning.
Advocate for the adoption of emerging AI technologies, analytical methodologies, and experimentation frameworks across the organization.
Communicate Impact to Leadership
Present analytical findings, model performance, and strategic recommendations to executive stakeholders.
Clearly articulate the business value and long-term implications of AI and machine learning investments.
Lead and Develop High-Performing Teams
Mentor, coach, and grow a team of Data Scientists through structured development, technical guidance, and career planning.
Foster a culture of collaboration, innovation, continuous learning, and engineering excellence.
Qualifications
Bachelor's degree or higher in Computer Science, Statistics, Mathematics, Engineering, Data Science, Physics, Economics, or a related quantitative discipline.
7+ years of experience in Data Science, Machine Learning, Artificial Intelligence, or Advanced Analytics, with a strong record of deploying production-grade solutions.
3+ years of leadership experience managing and developing technical teams.
Proven expertise in predictive modeling, segmentation, recommendation systems, classification, forecasting, optimization, and other statistical or machine learning methodologies.
Strong understanding of experimentation, causal inference, model governance, and performance evaluation.
Experience collaborating with product, business, engineering, analytics, and operational stakeholders in fast-paced environments.
Hands-on experience delivering end-to-end machine learning solutions, from problem framing and experimentation through deployment and monitoring.
Strong communication skills with the ability to influence both technical and non-technical audiences.
Nice to Have
Experience working with large-scale consumer platforms, digital products, subscription businesses, marketplaces, or other data-rich environments.
Familiarity with customer intelligence, personalization, lifecycle optimization, engagement analytics, or recommendation technologies.
Exposure to modern AI capabilities, including generative AI, large language models, or advanced decision intelligence frameworks.
Experience scaling data science functions, establishing operating models, and driving organizational adoption of AI-powered solutions.

Work arrangement
No