Manager Data Science

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  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.

• Building deep partnerships with product and business counterparts.

• Setting the team's roadmap, success criteria, and priorities in close collaboration with engineering and business partners.

• 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.

• Maintain a balance between building sustainable practices and going after high-impact projects on one hand and identifying low-cost, high-impact wins and intelligent scoping to deliver value sooner on the other.

• Coach and mentor our data scientists and data analysts technically and professionally.

• 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.

Qualifications

Technical Experience

• 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.

• Competence with reproducible data analysis using Python or R and excellent SQL skills.

• Comfortable with data modeling and dimensional design.

• 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 Big Query 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.

Qualifications

1. Bachelor's degree in engineering, computer science, technology, or similar fields.

2. A postgraduate degree is a plus but not required.

3. 5+ years of overall experience working in data science.2+ years of overall experience in leading data teams.

4. Experience doing data science in an online consumer product setting is a plus.

5. A good problem solver with a 'figure it out' growth mindset.

6. An excellent collaborator and communicator.

7. A strong sense of ownership and accountability.

8. A 'keep it simple' approach to #makeithappen.