Domino's Pizza is the largest pizza delivery and takeaway company in the world. Our expertise and passion for making and delivering fresh hot pizzas has won us numerous awards, but more than that we have the loyalty of millions of pizza lovers around the world.
The first Domino's Pizza store opened in 1960 in the state of Michigan in the United States. The success was so great that the company has since grown into a brand selling pizza in 90+ countries with more than 18,000 stores. The franchise formula has been established in the Netherlands since 1989 and now has 340+ stores.
Domino's Pizza Netherlands has been part of Domino's Pizza Enterprises Ltd (DPE) since July 2006. DPE is publicly traded in Australia and is the master franchisee for the Domino's Pizza brand in Australia, New Zealand, Japan, Taiwan, France, Luxembourg, Belgium, Germany, Denmark and the Netherlands.
The position of Data Scientist on the Group Strategy & Insights team represents an exciting opportunity to work for a world-leading QSR brand. This role will be based at Domino’s HQ in either Germany, France or the Netherlands. The role will provide support for Domino’s (DPE) markets, including ANZ, European and APAC markets.
We seek a candidate that is customer-focused, quantitatively savvy, and who can generate actionable insights from vast amounts of data leveraging Machine Learning and statistical techniques. A successful candidate will be a strong communicator and also have the ability to work cross-functionally within the Domino’s (DPE) organization.
You will be able to:
Leverage data and advanced analytic approaches to generate meaningful, actionable insights for the business. Compile insights and recommendations into clear, concise deliverables for internal business partners
Develop, implement and maintain predictive modeling and personalization algorithms (e.g. recommenders) to optimize customer experiences and drive revenue growth
Leverage Domino’s customer data and ML platforms to build customer analytics models and measure business-relevant customer metrics such as lifetime value, churn, frequency, etc.
Apply statistical techniques and machine learning approaches to a wide variety of business problems
Present results in a clear manner to senior leadership
A bachelor's degree in Statistics, Mathematics, Data Science, Computer Science, Engineering, or a field of similar quantitative nature;
At least 3 years of relevant experience in data science and/or machine learning;
The right papers to work in either Germany, France or the Netherlands;
Experience creating and using mathematical and machine learning methodologies such as: predictive modelling (using ML and GLM), time-series/forecasting analysis (prophet, ARIMA), scenario analysis, clustering (K-Means) and recommender techniques (item-to-vec, collaborative filtering;
Knowledge of advanced statistical techniques and concepts (properties of distributions, statistical hypothesis testing, experimental design) and experience applying these;
Proficiency in SQL;
Experience leveraging statistical programming languages R and/or Python for analyses (with in-depth knowledge of at least one);
Experience with data visualization tools, such as Tableau, Power BI, ggplot, seaborn; and experience articulating and presenting data, analyses, and technical concepts to a senior audience;
Knowledge of Cloud Technologies (AWS and Sagemaker);
Excellent written and verbal communication in English.
We are looking forward to your application! Please send us your CV (in English) and motivation letter.