This role focuses on identifying innovation opportunities around data and data-related processes to help clients implement fact-based decisioning processes within their cards and payments programs. It involves heavy focus on transaction data modeling and analytics for cards and payments products, collaborating with Business Managers, Consultants, and Data Scientists to strategize and deploy data-driven solutions. The position also emphasizes keeping the company at the forefront of technological advancement, developing next-generation analytic methods, and managing and growing talent within the team.
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Responsibilities
- Identify innovation opportunities around data and data-related processes to implement fact-based decisioning processes
- Collaborate with internal Technology partners and Data Engineering functions to leverage the company's internal technology platforms
- Develop next-generation analytic methods where existing tools are inadequate
- Review, guide, and inspire the analytical work of junior team members
- Manage and prioritize workload for self and direct reports to improve process efficiency
- Socialize innovative ideas and scalable approaches with market demand
Qualifications
- Minimum of 6+ years of expertise in applying Machine Learning solutions to business problems
- Post-graduate degree (Masters or PhD) in a quantitative field such as Statistics, Mathematics, or Data Science
- Experience in Card & Payments markets with specific responsibilities in payments or retail banking
- Good understanding of the Payments and Banking industry, including various card verticals
- Proven ability to deliver results within committed scope, timeline, and budget
- Very strong people/project management skills and ability to manage large projects
Technical Expertise
- Expertise in distributed computing environments/big data platforms (Hadoop, Elasticsearch, etc.)
- Strong programming ability in languages such as Python, R, SQL, and others
- Proficient in advanced data mining and statistical modeling techniques including Predictive modeling and Classification techniques
Work Conditions
This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.
