Lead Data Science Analyst

Lead Data Science Analyst

Requirements

• Bachelors Analytics, Engineering and Statistics or related
• 4+ years Credit Risk, Fraud Risk, Marketing Analytics, Optimization, Operations Analytics, Modeling/Data Science or related

Responsibilities

• Responsible for working closely with management to execute analytical initiatives.
• Responsible for solving business problem by leveraging techniques such as segmentation, optimization, advanced analytics and machine learning.
• Reviews and provides effective challenge to credit strategies including underlying assumptions, vintage analysis and expected impacts.
• Evaluate credit strategy performance against expectations and opine on source/cause of variances.
• Actively manages and escalates risk and customer-impacting issues within the day-to-day role to management.
• Conduct and support detailed review of credit strategy proposals using tools such as SQL, SAS, Python, Tableau, Snowflake.
• Leads the development and implementation of advanced analytics including customer segmentation, optimization, prescriptive analytics and machine learning algorithm & recommendation to solve business problems.
• Operates as a subject matter expert on statistical analysis, test and design of experiment, analysis methodology, modeling & application, and financial impact analysis.
• Collaborates with cross-functional partners to understand their business needs, formulate and complete end-to-end analysis that includes data gathering, analysis, ongoing scaled deliverables and presentations.
• Delivers effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.
• Establishes and maintains effective performance tracking; identify improvement opportunity, form hypothesis, proposes, designs and implements tests to drive strategy enhancement and optimization.
• Manages multiple priorities, communicate business performance and project progress to management & business partners.
• Develops and automates reports, iteratively build and prototype dashboards to provide insights at scale, solving for analytical needs.
• Facilitates implementation of work product and ensure accuracy.
• Consistently follows standard work processes and documentation requirements.
• Recommends improvement to work processes to increase efficiency while maintaining quality of work.
• Continuously improves technical and leadership skills through training and development.

Preferred Qualifications

• Masters Analytics, Engineering, Mathematics and Statistics