About the Role

Our client is a fast-growing technology company building the future of applied AI and data-driven products. Their solutions help enterprise organizations unlock efficiencies, automate decision-making, and deploy machine learning at scale. With strong early traction and an expanding customer base, they are scaling their data and product capabilities to meet increasing demand.
As Head of Data Science & Machine Learning, you will define and drive the organization’s data science vision. You’ll lead a team of data scientists, ML engineers, and analytics professionals to deliver high-impact insights, models, and products that shape both business strategy and customer outcomes.

Responsibilities

Strategic Leadership

• Define and execute the organization’s Data Science & Machine Learning strategy in alignment with overall business objectives.
• Establish the vision for how AI, machine learning, and advanced analytics create value across products and client solutions.
• Promote a culture of experimentation, measurement, and evidence-based decision-making.

Team Building & Leadership

• Recruit, mentor, and lead a multidisciplinary team of data scientists, ML engineers, and analysts.
• Foster a collaborative, innovative, and high-performance team environment.
• Set success metrics for the data science function and ensure accountability for outcomes.

Applied Data Science & ML Delivery

• Drive the design, development, and deployment of machine learning models (e.g., forecasting, personalization, recommendation, optimization).
• Oversee the integration of AI/ML solutions into products and customer platforms.
• Collaborate with Engineering and Product teams to deliver scalable, production-ready ML systems.
• Guide the adoption of modern data and ML tooling (e.g., Python, TensorFlow/PyTorch, Airflow, Snowflake/Databricks, dbt, Looker).

Data Governance & Democratization

• Ensure data quality, integrity, and compliance across all sources and pipelines.
• Lead initiatives to broaden access to data and enable self-service analytics across the organization.
• Embed responsible AI practices and ethical data use in partnership with key stakeholders.

Cross-Functional Collaboration

• Partner with Product, Engineering, and Business teams to translate complex, ambiguous problems into clear analytical questions and actionable insights.
• Provide executive-level guidance on data-driven strategy, including trade-offs and recommendations.
• Represent the company at industry events and thought-leadership forums focused on AI/ML and data science.

Requirements

• 10+ years of progressive experience in data science, machine learning, or advanced analytics, with at least 5 years in team leadership roles.
• Demonstrated success in designing, building, and deploying machine learning models into production at scale.
• Strong technical foundation in Python, SQL, modern ML frameworks (e.g., TensorFlow, PyTorch), and data engineering/orchestration tools (e.g., Airflow, Kubernetes, Terraform).
• Hands-on experience with modern data stack technologies (e.g., Snowflake, Databricks, dbt, Looker, Segment) and MLOps best practices.
• Deep expertise in statistical modeling, supervised and unsupervised learning, and applied AI methodologies.
• Solid understanding of data governance, compliance, and responsible AI principles.
• Excellent communication skills with the ability to translate complex technical topics into clear insights for business and executive stakeholders.
• Background in high-growth, fast-paced environments such as startups or scale-ups is strongly preferred.