Senior Data Scientist (Loyalty Analytics)
Job Summary
- Develop analytical and machine-learning solutions to improve member acquisition engagement retention and lifetime value.
- Build segmentation propensity recommendation uplift and optimization models for loyalty use cases.
- Design and analyze experiments including test-and-control frameworks and causal-impact measurement.
- Translate business questions into rigorous analytical approaches and actionable recommendations.
- Partner with product managers engineers analysts marketers and other data scientists to define priorities and deliver production-ready solutions.
- Establish success metrics and measurement frameworks for loyalty initiatives.
- Communicate findings clearly to technical and non-technical audiences including senior stakeholders.
- Promote high standards for data quality reproducibility model governance and responsible use of customer data.
- Contribute to the evolution of the organisations loyalty data platform and data products.
- Significant experience in data science advanced analytics or a closely related quantitative field.
- Strong programming skills in Python and SQL.
- Practical experience with statistical modelling machine learning experimentation and causal inference.
- Experience working with customer marketing CRM membership rewards or personalization data.
- Ability to work with large-scale complex and evolving data environments.
- Strong product sense and the ability to connect analytical outputs to customer and commercial outcomes.
- Excellent written and verbal communication skills.
- A collaborative pragmatic approach and a track record of delivering outcomes through cross-functional partnerships.
- Experience with loyalty travel marketplaces subscriptions rewards or customer lifecycle analytics.
- 8 years of experience in a similar analytical role.
- Experience developing models that influence customer journeys or marketing decisions.
- Experience taking models from prototyping through deployment monitoring and iteration.
- Graduate degree in statistics computer science operations research economics mathematics or a related quantitative discipline.
Competitive salary and performance-based bonuses.
Comprehensive insurance plans.
Collaborative and supportive work environment.
Chance to learn and grow with a talented team.
A positive and fun work environment.
Required Skills:
Python SQL Machine Learning Statistical Modeling A/B Testing Experimentation Causal Inference Customer Segmentation Propensity Modeling Recommendation Systems Customer Lifetime Value (CLV) Churn Modeling Marketing Analytics CRM Analytics Loyalty Analytics Personalization Predictive Analytics Data Science PySpark Spark Snowflake Databricks Tableau Data Visualization Model Deployment MLOps