- Company Name
- GOOD RECRUITER
- Job Title
- Head of Data science & engineering SAAS H/F
- Job Description
-
**Job Title**
Head of Data Science & Engineering (SaaS) – Female/Male
**Role Summary**
Lead and grow a 6‑person data team (Data Engineers, Data Scientists, DevOps) within a fast‑growing SaaS scale‑up in transport & logistics. Own the end‑to‑end data strategy, architecture, governance, and delivery of models, dashboards, and automation pipelines. Partner closely with Product, Engineering, and Business units to prioritize and align data initiatives with strategic business objectives.
**Expectations**
• Deliver a scalable, secure, and cost‑efficient data infrastructure.
• Modernize existing econometric models and introduce advanced AI techniques.
• Ensure high quality, well‑documented analytics and automated workflows.
• Communicate complex data concepts to stakeholders and clients in clear, non‑technical language.
• Provide regular strategic updates to executive leadership.
• Foster a collaborative, high‑performance team culture and drive professional growth.
**Key Responsibilities**
1. Manage, mentor, and inspire the data team; set hiring, development, and performance standards.
2. Define and execute the data strategy, architecture, FinOps, governance, security, and access controls.
3. Modernize and validate econometric and machine‑learning models; integrate new AI methods.
4. Oversee production pipelines, dashboards, and automation to maintain quality, documentation, and compliance.
5. Collaborate with Product, Engineering, and Business teams to prioritize, scope, and execute data projects.
6. Translate data insights into actionable business recommendations; engage with strategic clients.
7. Report data progress, risks, and opportunities to the executive committee and adapt plans accordingly.
**Required Skills**
- Proven leadership of cross‑functional data teams (5–10 people).
- Deep expertise in data engineering, machine‑learning, and AI model deployment.
- Strong understanding of scalable architectures, data lake/star patterns, and cloud platforms.
- Experience with FinOps, data governance, security frameworks, and compliance.
- Ability to translate technical findings into business value for non‑technical audiences.
- Excellent stakeholder management, communication, and presentation skills.
- Strategic thinking with a balance between technical depth (80%) and business insight (20%).
**Required Education & Certifications**
- Advanced degree (MSc/PhD) in Computer Science, Data Science, Statistics, or related field preferred, but not mandatory.
- Certifications in cloud data services (AWS, Azure, GCP), big‑data platforms (Spark, Hadoop), and data governance/practice frameworks (CDMP, DAMA) are strong advantages.