Product Data Scientist II (Based in Dubai, UAE) at Delivery Hero

Dubai, Dubai, United Arab Emirates -

Full Time

Start Date

Immediate

Expiry Date

11 Jan, 26

Salary

0.0

Posted On

13 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, R, Data Modeling, Data Analysis, Statistical Techniques, Experiment Design, Data Profiling, KPI Design, Collaboration, Communication, Problem Solving, Machine Learning, BigQuery, Data Engineering, Data Pipeline Development

Industry

technology;Information and Internet

Description

Company Description Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region. We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily. At talabat, we foster an innovative environment where our talabaty employees can strive to create a positive impact across the region through the use of our platform. Job Description Role Summary As the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users. As a data scientist on the analysis track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain including logging, data modeling, analysis, reporting, and experimentation. 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 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. Qualifications Bachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required. 3+ years of overall experience working in data science and machine learning. Experience doing data science in an online consumer product setting is a plus. A good problem solver with a ‘figure it out’ growth mindset. An excellent collaborator. An excellent communicator. A strong sense of ownership and accountability. A ‘keep it simple’ approach to #makeithappen.

Responsibilities

As a data scientist, you will improve decision-making across product and business using reliable data. You will manage the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.