Full-Time

Analytic Science-Sr Director

Posted on 11/21/2024

FICO

FICO

Compensation Overview

$175k - $275kAnnually

Senior

Remote in USA

Category
Data Science
Data & Analytics
Required Skills
Python
R
Customer Service
Natural Language Processing (NLP)
Data Analysis
Requirements
  • This position requires a Master’s degree or equivalent in Mathematics, Statistics, Computer Science, or related field, and 10+ years of related experience in the financial services industry, ideally in credit risk.
  • Proven project management experience pertaining to the research, development, and delivery of analytic solutions.
  • Experience leading cross functional teams of analysts/scientists, software developers, and business stakeholders in execution of analytic projects (including people management experience).
  • Strong statistical and analytic skills, including fluency with at least one of SAS, R, and/or Python, and practical, in field experience with cutting edge machine learning techniques such as Stochastic Gradient Boosting and Natural Language Processing.
  • Extensive client-facing experience, including creating and leading pre-sales and delivery presentations to customers about analytic solutions and innovations.
  • Knowledge of alternative (non-traditional) credit data sources, including experience with the development of meaningful predictors off of those sources, and with optimizing the use of predictors from multiple data sources in combination with each other to drive predictive and robust models.
  • This position requires travel (domestic and international) less than 10% of the time.
Responsibilities
  • Provide thought leadership as well as day-to-day management of key analytic product support and development efforts in the Scores group, ensuring top quality work product while meeting delivery expectations.
  • Partner with business development and client services teams offering technical (Analytics) expertise on risk management topics such as credit scoring, underwriting strategy definition, and alternative data sources.
  • Hands-on development of predictive models, leveraging expertise with different types of predictive modeling techniques including machine learning algorithms.
  • Present findings and project status to higher level management internally and evangelize our products and research findings externally in client discussions as well as presentations at industry and/or academic conferences.
  • Manage relationships and expectations effectively by ensuring high level of customer service/support is provided to 'customers', whether internal or external.
  • Respond to any technical questions from clients about our Scores products in a way that confirms deep mastery of our products as well as expertise in the credit risk modeling field more generally.
  • Day-to-day analytic management of research projects aimed at developing new analytic insights and products or enhancing existing Scores products; working with IT/programming to ensure quality of data received, devising and executing research plans (often by leading teams of analysts), and leveraging the results to help define an analytic roadmap pertaining to the product in question.

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

N/A