Data Scientist - Customer Analytics
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Key skills for this role
About the Role
Payolab seeks a Data Scientist with 3+ years of experience in customer analytics, ideally in financial services. You will develop predictive models, extract insights from complex data sets, and collaborate with cross-functional teams.
Key Skills for This Role
Responsibilities
- Develop, test, implement, and maintain predictive models
- Identify opportunities to innovatively use data / extract insights from complex data sets
- Collaborate with cross functional teams to understand business requirements
- Document all steps in the development process
- Stay updated with the latest developments in the field
Requirements
- 3+ years in a similar role, ideally with financial services
- Advanced knowledge of statistical analysis and machine learning
- Highly proficient in SAS programming language (SAS 9.4)
- Proficient in other data science programming languages (e.g. Python, R)
- Experience in Dataiku and understanding of MLOps (on Azure)
- Strong communication skills and ability to present findings to senior stakeholders (non technical)
- Experience in financial industry will be an advantage
- Collaborate with cross functional teams to understand business requirements
- Document all steps in the development process
- Stay updated with the latest developments in the field
Full Job Posting
Knowledge & Experience
- 3 years + in a similar role, ideally with financial services.
- Advanced knowledge of statistical analysis and machine learning.
- Highly proficient in SAS programming language (SAS 9.4).
- Proficient in other data science programming languages (e.g. Python, R).
- Experience in Dataiku and understanding of MLOps (on Azure).
- Experience in financial industry will be an advantage.
- Strong communication skills and ability to present findings to senior stakeholders (non technical).
Requirements Non technical
- Strong communication skills and ability to present findings.
- Experience in financial industry.
- Collaborate with cross functional teams to understand business requirements.
- Document all steps in the development process.
- Stay updated with the latest developments in the field.
Requirements Technical
- Advanced knowledge of statistical analysis and machine learning.
- Highly proficient in SAS programming language (SAS 9.4).
- Proficient in 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.
Cultural fit
- Owning the outcome (ownership).
- Being driven/passionate in analytics.
- Problem solving mindset, challenging the status quo.
- Self organizing, independent and takes ownership of each task.
- Meticulous to detail.
- Thrive under pressure.
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.
- Collaboration effectiveness.
- Data security compliance.
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