This job is no longer available
This job expired on 13/09/2026. It no longer accepts applications.
Data Scientist: Product & Analytics
Jobgether
Job description
About the role
We are looking for a Data Scientist focused on Product & Analytics to turn complex data into actionable insights that drive product decisions and improve user experiences at scale. Based in Ireland, you will work at the intersection of data science, analytics engineering, and product strategy, building reliable data products and designing experiments that influence millions of interactions.
Key responsibilities
- Build, maintain, and enhance production data products and analytical systems supporting key business decisions.
- Design and analyse experiments with Product and Growth teams, define success metrics and deliver actionable recommendations.
- Develop robust analytical foundations through data modelling, pipeline improvements, data‑quality monitoring and scalable analytics solutions.
- Partner with stakeholders to understand complex business challenges, explore data, identify opportunities and propose effective solutions.
- Translate complex analyses into clear insights for technical and non‑technical audiences.
- Continuously improve analytics infrastructure, semantic data models, experimentation frameworks and future data‑driven capabilities.
- Collaborate with Data Engineering teams to strengthen the overall data platform and ensure trusted, accessible information.
Required profile
- Several years of experience as a Data Scientist, preferably in a product‑focused or technology‑driven environment.
- Strong ownership mindset with the ability to work independently and navigate ambiguous problems.
- Proven track record of delivering production data products or analytical systems that generate measurable business impact.
- Experience collaborating directly with Product, Growth, Marketing or other business teams to solve strategic problems.
Required skills
- Python programming
- SQL
- Data warehousing and transformation tools (e.g., dbt)
- Analytics platforms
- Statistical analysis and hypothesis testing
- Experimentation methodology
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