About the Team
We’re rethinking the way AB InBev does business with its retail customers and creating digital experiences to serve them. You will be joining a new digital organization within AB InBev consisting of digital strategy, product, design, analytics, operations and engineering. This organization is responsible for building the products and platforms that transform our traditional sales operations across the world.
About the Job
The Data Scientist will be responsible for mining, exploring and discovering our sales data in order to create algo to test insights to transform our ways of working and improve our NPS and sales with the point of sales.
- Support Product Marketing, Partner Development, and the Executive Team with analytics for product performance and customer insight.
- Forecast performance and yield by customer cohorts; create propensity models to drive marketing and sales strategies.
- Empower the global Partner Development teams with insights to advise and fulfill their strategic objectives and goals.
- Quantify the impact of product, sales, and marketing initiatives on customer satisfaction and future behavior.
- Design and evaluate experiments that help define opportunities for increased usage, improved marketplace performance, and greater customer happiness.
- Monitor usage metrics and provide business-based explanations for large scale trends and patterns in customer lifecycle behavior. Detect and surface anomalies.
- Develop reusable models and assets working closely with Data Technology team to ensure scalability and industrialization as models move into production.
- Lead business analytic projects and initiatives through all phases, including defining investigations, exploring data, analysis, interpretation, and presentation of results and work you're doing.
We're looking for a hardworking and passionate person to join this amazing team, if this resonates, we'd love to hear from you!
- 6+ years of recent experience in a data science role. Preferably experience in the digital advertising industry or related field.
- Ability to operate comfortably and effectively in a fast-paced, highly multi-functional, rapidly changing environment.
- Programming skills in Python, R and SQL, and comfortable with advanced analytics tools such as R, Spark, and Power BI. Experience with the Microsoft Azure platform and Hadoop infrastructure.
- Deep knowledge in Microsoft Machine Learning and Microsoft Cognitive Services is a must.
- Ability to communicate the results of analyses in a clear and effective manner with product and leadership teams to influence the overall strategy of the product.
- Ability to work with engineering partners to meet the data needs of the business, translating business needs into analytical requirements.
- Experience in quantitative analysis including regression, classification, clustering, and time-series analyses.
- Confirmed experience with end to end implementation of a model prototype specifically processing, feature engineering, and model outputs.
- Comfortable working with modern data technologies and familiarity with database modeling and data warehousing principles.
- Practical experience working with and conducting experiments on large datasets!