A financial services company in Abu Dhabi is looking for a Data Scientist with strong SAS and programming skills. The role involves developing predictive models and collaborating across teams to solve business problems. Suitable candidates will have over 3 years of experience and a strong understanding of statistical analysis. Excellent communication skills are essential. An ownership mindset and ability to challenge status quo will be valued.
Formación
3+ years in a similar role, ideally in financial services.
Advanced knowledge of statistical analysis and machine learning.
Highly proficient in SAS programming (SAS 9.4).
Proficient in other Data Science programming languages (Python, R).
Experience with Dataiku and MLOps on Azure.
Strong communication skills for presenting findings.
Responsabilidades
Collaborate with cross-functional teams to understand business requirements.
Document all steps in the development process.
Develop, test, implement, and maintain predictive models.
Identify opportunities to innovatively use data.
Conocimientos
Statistical analysis
Machine learning
SAS programming
Python
R
Dataiku
MLOps
Strong communication skills
Descripción del empleo
About the job Data Scientist- Customer Analytics
Term: 5 months
Job location: Abu Dhabi & Offshore
Experience requirement:3 years +
Project scope: Data Scientist Customer Analytics
Number of resources: 1
Role:
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
Technical
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
Cultural Fit
Owning the outcome (ownership)
Problem solving mindset, challenging the status quo
Self-organizing, independent and takes ownership of each task
KPIs:
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:
3years + 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 is 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)
* El índice de referencia salarialse calcula en base a los salarios que ofrecen los líderes de mercado en los correspondientes sectores. Su función es guiar a los miembros Prémium a la hora de evaluar las distintas ofertas disponibles y de negociar el sueldo. El índice de referencia no es el salario indicado directamente por la empresa en particular, que podría ser muy superior o inferior.