About the Team
The Be Group Data organization owns the end-to-end data, modeling and AI foundation serving every business line at beGroup — Transport, Food, Delivery, Fintech and others. The Data Science & AI side builds the models and intelligent systems the marketplace runs on — matching and dispatch, arrival-time estimation, dynamic pricing, search, recommendation and personalization — alongside a growing portfolio of agentic systems. We run on Google Cloud (BigQuery, Airflow, dbt/Dataform) with an emerging LLM/agent platform.
About the Role
The Head of Data Science & AI owns the models & intelligence side of the Data organization — building models and production systems to move the company's core business metrics. Your top priority is delivering the strategic AI initiatives into production while keeping the core data-science engines on target.
The role leads three broad areas of work:
- Marketplace decision engines — the live models driving the company's core partnerships (rider, drivers, sellers), kept on target and continuously improved.Search, recommendation & personalization — ranking and personalization across the app's surfaces.
- Applied AI & agentic systems — a portfolio of LLM-based agents and assistants spanning operations, customer support and marketing/growth, delivered on an internal platform for hosting and governing them.
You own the outcomes by leadership and technical contributions.
Job Responsibilities
- Data-science engines. Own the roadmap and targets for live models and their production systems — and balance them against strategic initiatives (new business cases, models and tooling) so business-as-usual doesn't crowd out higher-value work.
- Applied-AI & agentic delivery to production. Deliver agentic use cases from design to production, while building out the internal AI platform (agent-hosting platform, ontology, agent stable).
- Governed AI/LLM consumption. Own the team's centralized LLM/AI usage with per-system cost visibility, access controls and ontology governance.
- Cross-functional delivery. Be the senior data-science / AI counterpart to product, engineering and business heads; represent shared model and data needs so cross-cutting work isn't stuck behind any single team's backlog.
- People leadership. Lead and grow the data-science / AI leads and their teams (data scientists, ML/AI engineers); manage workload, hiring and quality; represent the Data Science & AI organization to senior leadership and cross-functional partners.
Requirements
Must-have
- 5+ years leadership experience with data-science / ML teams that shipped production models with measurable business impact.
- Hands-on experience and expertise in one or several of the following areas: personalization & recommendation, optimization, forecasting or causal inference.
- Proficiency with designing and analysis of concurrent experimentations (A/B, canary, holdout, uplift), plus management of the model lifecycle / MLOps.
- Hands-on or close leadership experience with applied-AI / LLM use cases — taking LLM-based agents or assistants to production with quality bars and guardrails.
- Strong cross-functional leadership and communication — able to align product, engineering and business leaders behind specific problems and solutions, and to elaborate / drive data science and AI roadmaps.
Preferred
- Deep technical expertise in dynamic optimization, reinforcement learning or causal inference.
- AI engineering / LLM depth — agent harness design, ontology construction, access governance, evaluation frameworks, and observability / tracing. Data / AI strategy and operating-model design.
