Principal Data Scientist

Key Skills

Algorithms, Big Data Technology, Data Analytics, Data science techniques, Effective communication skills, Finance, KPI, Machine learning techniques, PySpark, Python Programming, R Programming, SAS, Scala Programming, SQL, Statistical modeling

Job Description

Why We Work at Dun & Bradstreet

Dun & Bradstreet unlocks the power of data through analytics, creating a better tomorrow. Each day, we are finding new ways to strengthen our award-winning culture and accelerate creativity, innovation and growth. Our 6,000+ global team members are passionate about what we do. We are dedicated to helping clients turn uncertainty into confidence, risk into opportunity and potential into prosperity. Bold and diverse thinkers are always welcome. Come join us!

• The Principal Data Scientist will utilize advanced analytics, statistical, and big data tools and data-driven methodologies to support the development of D&B’s next-generation business solutions.

• This role will work with internal and external D&B clients and stakeholders to identify their business needs and opportunities, to develop, implement, manage analytics solutions, and to improve business outcomes in D&B Finance & Risk Solutions business unit.

• The Principal Data Scientist will perform statistical analysis and set strategic direction and plan of execution based on insights gained through data analysis and customer feedback to drive meaningful business results.

• The Principal Data Scientist will participate in all aspects of a modeling engagement, including design, development, validation, calibration and documentation.

• The Principal Data Scientist will research complex business issues and recommend solutions, including model inputs, framework, analytics solution design and end products.

• The Principal Data Scientist will serve as a Subject Matter Expert on predictive models within the Analytics team and with business users; consult with the business, as appropriate, on predictive modeling solutions.

• The Principal Data Scientist will validate the performance of existing quantitative risk models, to ensure that key KPIs are set and attained, and to recommend changes when necessary.

• This resource will drive timely retrieval of risk analytics data from existing systems to create algorithms that meet business needs.

• This role involves the opportunity to telecommute from within the Jacksonville, FL area up to three (3) days per week, as feasible. 

Position Requirements

• Master’s degree in Statistics, Mathematics, Economics or a related quantitative field (U.S. or foreign degree equivalent) plus five (5) years of progressively responsible, post-baccalaureate experience in the job offered or in a related advanced statistical or data analytics role.
• Five (5) years of experience in/with: utilizing Scorecard Modeling Technique and Logistic Regression, performing data analysis and data mining including univariate distribution, bivariate analysis, and descriptive statistics; utilizing programming tools including R or SAS; performing research utilizing Python to manipulate data and conduct statistical analysis; utilizing SQL to work with large data sets and develop risk models; performing loss forecasting including Comprehensive Capital Analysis and Review (CCAR), Internal Capital Adequacy Assessment Process (ICAAP), and Current Expected Credit Loss Model (CECL); utilizing Basel Economic Capital Models including probability of default (PD), exposure at default (EAD), and loss given default (LGD); and working with Machine Learning and Artificial Intelligence tools to create new-generation of risk scores and models to meet business needs for clients.
• Three (3) years of experience with: working with Mortgage, Retail & Wholesale business banking for risk model development experiences to improve accuracy of loss forecast and reserves; developing strategies for new business risk solutions; utilizing linear regression, predictive modeling, and behavior modeling techniques; performing pricing analytics as well as Risk appetite and Industry analysis segments for Business Banking customers, performing model validation and computing model performance statistics like ROC, KS and Gini coefficient; and working with collections models, recovery models, loan origination models, and portfolio account management models.
• Two (2) years of experience working with Markov Chain State Transition Models and Rating Migration models to determine probability of default.
• Must have demonstrated ability to explain complex and advanced analytics concepts to technical and non-technical audience, as well as building and maintaining relationships with clients.

Benefits We Offer

• Generous paid time off in your first year, increasing with tenure.
• Up to 16 weeks 100% paid parental leave after one year of employment.
• Paid sick time to care for yourself or family members. 
• Education assistance and extensive training resources.
• Do Good Program: Paid volunteer days & donation matching.
• Competitive 401k & Employee Stock Purchase Plan with company matching. 
• Health & wellness benefits, including discounted Gympass membership rates.
• Medical, dental & vision insurance for you, spouse/partner & dependents.