Data Scientist – Customer Analytics

Role:

Advanced knowledge of statistical analysis and machine learning
Highly Proficient in SAS programming language (SAS 9.4)
Proficient is other Data Science programming languages (e.g. Python, R)
Experience in Dataiku and understanding of MLOps (on Azure)
Develop, test, implement, and maintain predictive models
Identify opportunities to innovatively use data/ extract insights from complex data sets

KPIs:

Time to deployment
Model accuracy (e.g., RMSE, MAE for regression tasks)
Number of business problems addressed
Responsiveness to business questions/problems/requests
Number of departments/business users supported/adopted the solution
Stakeholder Satisfaction: The level of satisfaction of stakeholders with the reports and insights provided.
Collaboration Effectiveness: The effectiveness of collaboration with cross-functional teams, measured through the quality of insights extracted.
Data Security Compliance: Compliance with data security protocols and regulations.

Knowledge & Experience:

Strong communication skills and ability to present findings to senior stakeholders (non technical)

​​​​​​​​​​​​​​Data Scientist

Data Scientist