Data Modeling and Analysis: Develop and implement sophisticated data models to support initiatives such as customer journey mapping, propensity modeling, and personalization implementation.
Forecasting and Predictive Analytics: Utilize statistical and machine learning techniques, including logistic regression, random forests, and ensemble modeling to create accurate forecasts and predictive models.
Incrementality Analysis: Conduct robust incrementality analyses and causal impact studies to measure the effectiveness of various marketing strategies.
Model Management: Oversee the full lifecycle of data science models from development to deployment (in conjunction with our Data Engineering Team) and maintenance, ensuring high performance and scalability.
BI and Analytics Development: Design and enhance BI tools and analytics frameworks to improve data visualization, reporting efficiency, and decision support across the organization.
Collaboration and Insight Presentation: Work closely with cross-functional teams to translate data-driven insights into actionable business strategies. Communicate complex results to non-technical stakeholders effectively.
Requirements & Skills:
Business stakeholder engagement to understand their pain-points, identify opportunities, and develop analytical solutions that can create value for them, solving their most difficult problems and adjusting the communications style to successfully influence them.
Professional experience in a data science position, with a proven track record of implementing and managing advanced models in a business environment.
Prior experience in developing data science capabilities & driving its consumption.
Utilisation of data to discover insights, predict behaviour, add value and visualise results and patterns to provide recommendations to support Cashrewards’ ambitions.
Expertise in programming languages such as Python and SQL. Familiarity with cloud services is preferred.
Experience with building dashboards in either Power BI or Tableau
Experience of building and implementing personalization models is highly preferable.
Understanding of Marketing Technologies such as Adobe Analytics, Braze, Kevel or Salesforce is highly preferable.
Working with large datasets and click-stream data in the past is required. Experience with Retail/CPG/Advertising/Media analytics, Customer analytics, Marketing analytics is preferred
