24 mrt 2026
Product Analyst - Temporary
| Branche | Zie onder |
| Dienstverband | Zie onder |
| Uren | Zie onder |
| Locatie | Utrecht |
| Opleidingsniveau | HBO / bachelor |
| Contactpersoon |
Shir Abramovich |
Informatie
- Provide analytical support across multiple Product teams.
- Collaborate with Product Managers to set and track Objectives and Key Results (OKRs).
- Define metrics for new and existing products in partnership with Product Managers and Designers.
- Identify product opportunities based on analysis of existing data points.
- Develop new insights to prioritize product development initiatives.
- Design and analyze experiments to validate product hypotheses and assess impacts.
- Validate the impact of implemented solutions on product performance.
- Create and maintain data models that effectively support team needs.
- Foster strong stakeholder relationships and effectively collaborate with cross-functional teams.
Omschrijving
- Provide analytical support across multiple Product teams.
- Collaborate with Product Managers to set and track Objectives and Key Results (OKRs).
- Define metrics for new and existing products in partnership with Product Managers and Designers.
- Identify product opportunities based on analysis of existing data points.
- Develop new insights to prioritize product development initiatives.
- Design and analyze experiments to validate product hypotheses and assess impacts.
- Validate the impact of implemented solutions on product performance.
- Create and maintain data models that effectively support team needs.
- Foster strong stakeholder relationships and effectively collaborate with cross-functional teams.
Functie eisen
- Bachelor’s degree in Data Science, Statistics, Mathematics, Economics, Business, or a related field;
- 3+ years of experience as an analyst in a product environment;
- Proficiency in SQL, Git, and dbt (essential);
- Familiarity with programming languages such as Python;
- Experience with data visualization tools, preferably Looker;
- Knowledge of data orchestration tools like Airflow;
- Familiarity with BigQuery and Jupyter Notebooks;
- Strong foundation in statistical concepts;
- Ability to employ advanced analytics techniques to establish causal relationships (e.g., A/B testing, difference-in-differences, causal inference);
- Experience in metric definition and performance tracking.
- Proficiency in creating and maintaining data models to meet team needs.
- Strong stakeholder management skills to enable effective collaboration across different teams.
