Data Science

Senior Data Science Engineer

We are seeking a talented Data Scientist with strong expertise in SAS Viya and significant experience in
the banking and telecom sectors. In this role, you will leverage advanced analytics and machine learning
techniques to derive actionable insights from large datasets, optimizing business decisions and
strategies. Your knowledge of SAS Viya, along with your domain expertise, will be essential for
developing predictive models, improving customer experience, and enhancing operational efficiency. 

Description

• Develop, implement, and fine-tune predictive and statistical models using SAS Viya to address
  business needs, with a focus on customer segmentation, churn prediction, fraud detection, and
  risk management in the banking and telecom sectors.
• Conduct deep data analysis and feature engineering to uncover patterns, trends, and insights
  that drive business strategies in banking and telecom operations.
• Integrate and process large datasets from various sources (e.g., transactional data, customer
  behavior data, financial data) and leverage SAS Viya’s cloud-native capabilities for scalable data
  processing and analysis.
  
• Apply machine learning algorithms and artificial intelligence techniques to develop models that
  enhance customer experience, optimize marketing campaigns, and improve operational
  efficiency.
• Present findings and insights through clear and actionable visualizations and reports using SAS
  Visual Analytics and other reporting tools, making complex data accessible to stakeholders.
• Continuously improve model performance by fine-tuning algorithms and optimizing data
  workflows to handle large volumes of data efficiently.

Requirements

• 5+ years of experience as a Data Scientist with a strong background in SAS Viya and experience
  working in banking and telecom sectors..
• Strong proficiency in SAS Viya (including SAS Visual Analytics, SAS Visual Data Mining and
  Machine Learning, and SAS Cloud Analytics).
• Experience with predictive modeling, statistical analysis, and machine learning algorithms in
  both sectors.
• Excellent communication skills, with the ability to translate technical findings into business
  insights for non-technical stakeholders.