Job Description
We are on the lookout for a Specialist, Data Scientist - Marketing to join the Central Marketing Analytics Team on our journey to always deliver amazing experiences.
Join the team driving brand growth and customer engagement across our markets. As part of our Marketing Analytics Team, you’ll help shape strategies that build customer loyalty and optimize the effectiveness of our marketing investments. With each model, framework or analysis, you’ll play a key role in creating connections with millions of customers, positioning Delivery Hero as a leader in the market.
1. You will drive the decision-making process on Marketing topics such as customer acquisition, retention or upselling across all Delivery Hero brands by using analytics, statistics, visualization and data science
2. You will work closely with the wider Marketing teams to drive innovation by analyzing customer data, prototyping solutions and models, and establishing steering metrics.
3. Drive the development and implementation of statistical, machine learning, and optimization models for choice optimization, rider fleet busyness and travel time prediction, and demand control. Collaborate with cross-functional teams to enhance the efficiency and performance of the machine learning models across the vertical.
4. Analyse large-scale datasets to understand and identify opportunities by deploying sophisticated statistical techniques to improve decision-making in the domain.
5. Define and drive the best practices of analytics and statistics within the Marketing and product analytics domain as well as be the guardian of these best practices in front of stakeholders.
Qualifications
6. You excel at modelling business problems using machine learning techniques, covering feature engineering, model selection, design, evaluation and optimisation to deliver value to the business.
7. You have strong business acumen: the ability to look at a business problem and translate it into data, as well as the ability to transform analysis results into practical insights and operational recommendations.
8. You possess knowledge of a wide variety of analytics and statistical methods (, Causal inference, Clustering, and Propensity Modelling) and their pros and cons. You can identify the best approach and methods suitable for a problem.
9. You have expertise in building and training machine learning models with strong knowledge of the Python data toolkit, ideally centring around Pandas, SQL, Sklearn, and PySpark.
10. Through the fluent use of SQL queries, you are able to explore our data universe and gather data to support your analysis and the development of machine-learning solutions.
11. You have effective communication skills and the ability to explain complex work in simple terms to team members and stakeholders, as well as visualize data to reinforce insights.