Data Scientist (R-17065)

Requirements:

• Ph.D. or Masters in a quantitative / applied field (Statistics, Econometrics, Computer Science, Operations Research, Mathematics, Engineering) with 3+ years of applicable experiences. 
• Strong knowledge and experiences Machine Learning and AI and its application.
• Strong programming skills with the ability conduct research utilizing Python, PySpark and other tools to manipulate data and conduct statistical analysis.
• Strong SQL skills and experience.
• Strong client collaboration skills, including the ability to build and maintain relationships with clients.
• Ability to effectively communicate complex ideas to both a technical and non-technical audience.
• Strong knowledge of MS office tools.

Essential Responsibilities

• Work with decision-makers across the company or external clients to understand their business goals, identify opportunities to use data and analytics to develop new insights, and to improve business results.
• Participate in all aspects of a modeling engagement, including design, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting.
• Validate the performance of existing quantitative risk models, to ensure that key KPIs are set and attained, and to recommend changes when necessary.
• Grow into a Subject Matter Expert over time on predictive models within the Analytics team and with business users; consult with the business, as appropriate, on predictive modeling solutions.
• Partner with internal D&B team to develop new business solutions in risk analytics.
• Experience managing multiple projects to meet challenging timelines.

Preferred Qualifications

• Strong business acumen, especially in Financial Services Industry Experience in underwriting, risk, statistical modeling roles.
• Experience working with very large datasets. 
• Experience applying modern machine learning techniques.
• Solid understanding of machine learning and explainability.
• Strong technical writing skills.