Director of Data Science

Key Skills

Business Intelligence, Data Analytics, Data science techniques, Design, Java Programming, Leadership, Management, Python Programming, R Programming, Random forests, SAS, SQL, XGBoost

Job Description

The Credit Services Risk Management team is a large and complex critical function for company success. The team is highly-skilled and motivated with a large emphasis on analytical abilities & problem solving skills. The Director of Data Science will lead and grow a data science team to build and maintain predictive models used for underwriting and/or collections functions. This person will lead the research and recommendations of new data sources to improve models and design tests to measure the effectiveness of various strategies implemented.

MAJOR DUTIES AND RESPONSIBILITIES

• Lead the data science team to implement models in production and conduct post-launch testing and enhancement
• Actively and consistently supports all efforts to simplify and enhance the customer experience
• Responsible for the selection of appropriate algorithms and execution
• Responsible for interpretation of results – for both causal inferences and predictive effectiveness
• Synthesize appropriate recommendations for action and changes
• Present findings, suggested actions and changes to a broad audience, and manage follow-ups and execution
• Help teach and explain techniques and tools used to a broad set of business-intelligence, data, and analytics professionals with varied backgrounds
• Provide coaching and mentoring to achieve a high-performing team
• Manage internal client relationships, including issue resolution, and overall accountability for results and client satisfaction
• Exercise thought leadership and discretion in tailoring the tools, approaches, and data used to meet the needs of the particular problem
• Perform other duties as required

QUALIFICATIONS

• Skills / Abilities and Knowledge
• Expert level skills and experience with using programming languages such as SAS/Python/R
• Expert level skills and experience with building Logistic Regression models, Random Forest models, XGBoost models, and Experimental Design
• Solid understanding of the theoretical background of each statistical test and model, inside and out
• Strong synthesis and presentation skills
• Expert-level logical thinking skills
• Education
• B.S. in quantitative sciences, including statistics, engineering, computer science or business with focus on analytics. M.S. or Ph.D. in Statistics or Data Science will be highly preferred.

Related Work Experience

• Statistical Analysis - 10+
• Business Analysis - 8+
• SAS/Python/R Programming - 8+
• Management and Supervision (general leadership and management experience in the field of analytics and/or data management) - 5+
• Internal client relationship management - 5+
• Database Design or Database Modeling - 2+
• Industry experience in Financial services, insurance or actuarial services preferred but not required