Data Scientist Full-time Job
2 weeks ago IT & Telecoms Dubai 79 views Reference: 32733Job Details
What’s On Your Plate?
Leveraging ambiguous business problems as opportunities to drive objective criteria using data.
Developing a deep understanding of the product experiences and business processes that make up your area of focus.
Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.
Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.
Working closely with product and business teams to identify important questions that can be answered effectively with data.
Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision making through deep analysis and automated reports.
Designing, planning and analyzing experiments (A/B and multivariate tests).
Supporting product and business managers with KPI design and goal setting.
Mentoring other data scientists in their growth journeys.
Contributing to improving our ways of work, our tooling, and our internal training programs.
What you need to be successful
What Did We Order?
Technical Experience
Excellent SQL.
Competence with reproducible data analysis using Python or R.
Familiarity with data modeling and dimensional design.
Strong command over the entire data analysis lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.
Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.
Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.
Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).
Familiarity with BigQuery and the Google Cloud Platform is a plus.
Data engineering and data pipeline development experience (e.g. via Airflow) is a plus.
Experience with classical ML frameworks (e.g. Scikit-learn, XGBoost, LightGBM, ...) is a plus.