Data Science Manager

Job Description

Responsibilities:

• Serve as an analytics expert in designing, developing and implementing best in analytic solutions
• Create and deliver powerful insights from data through better visualization and storyboarding
• Collaborate with internal and external partners to fully understand business requirements and desired business outcomes
• Demonstrate execution proficiency in handing multiple medium-to-large analytics projects in a team environment that includes the rest of the Data Science team
• Draft detailed scope for assigned projects, addressing suggested methodology and analytics plan
• Execute on the analytics plan with appropriate data mining and analytical techniques
• Perform quality assurance of data and deliverables for work performed by other Data Scientists and self
• Ensure all project documentation is up to date and all projects are reviewed per analytics plan
• Ensure project delivery within timelines and budget requirements
• Build on teams analytical skills and business knowledge
• Enhance existing analytics techniques by promoting new methodologies and best practices in the Data Science field
• Provide subject matter expertise and quality assurance of complex data-driven analytic projects

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Qualifications

• Minimum of 5-7 years of analytics expertise in applying statistical solutions to business problems
• Experience working in one or more of the Card Payments markets around the globe
• Post-graduate degree (Masters or PhD) in a Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics, Engineering, or equivalent
• Good understanding of the Payments and Banking Industry including aspects such as consumer credit, consumer debit, prepaid, small business, commercial, co-branded and merchant
• Good knowledge of data, market intelligence, business intelligence, and AI-driven tools and technologies
• Experience planning, organizing, and managing multiple large projects with diverse cross-functional teams Building ML models, Advanced Analytics, Python, Pyspark,
• Demonstrated ability to incorporate new techniques to solve business problems
• Demonstrated resource planning and delivery skills