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Important information
Contract type:
Permanent contract
Salary:
Salary according to profile
Location:
Casablanca, Morocco
Starting date:
2 to 4 weeks
Work mode:
Hybrid, Onsite
Published on:
28 April 2026
What they need
Context
Collective.work is building the next-generation AI-powered sourcing platform for recruiters. Our mission is to help talent teams identify, engage, and hire the best candidates faster through intelligent automation and data-driven insights. We operate at the intersection of data, AI, and recruiting workflows—where analytics plays a key role in shaping product decisions and user impact.
Missions
- Analyze user behavior, product usage, and funnel performance to generate insights
- Build dashboards and reports to track key metrics (acquisition, engagement, retention)
- Design and evaluate A/B tests and experiments
- Partner with product and engineering teams to define KPIs and success metrics
- Translate complex data into clear, actionable recommendations
- Support data-driven decision-making across product, growth, and operations
- Ensure data quality and consistency in reporting
- Contribute to building a strong data culture across the company
Tools & Environment
- SQL (advanced)
- BI tools (e.g., Looker, Metabase, Tableau)
- Python or R (nice to have)
- Data warehouses (BigQuery, Snowflake, Redshift)
- Product analytics tools (e.g., Amplitude, Mixpanel)
Working Conditions
- Flexible remote work environment
- Opportunity to grow with a scaling company
- High impact role influencing product and business decisions
- Collaborative, data-driven culture
Profile wanted
- 2–4+ years of experience in data analysis or a similar role
- Strong SQL skills and experience working with large datasets
- Experience building dashboards and data visualizations
- Solid understanding of product metrics and analytics frameworks
- Experience with experimentation and A/B testing
- Ability to communicate insights clearly to non-technical stakeholders
- Strong analytical thinking and problem-solving skills
- Attention to detail and data quality
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