This role involves developing and validating predictive models, engaging stakeholders, automating business processes using data science techniques, and recommending solutions for complex business issues.
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! Learn more at dnb.com/careers.
The Role:
As part of Dun & Bradstreet's Data & Analytics team, you will participate in all aspects of modeling engagement, including design, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting. You will research complex business issues and recommend solutions, including model features, end products and any data required to support growing Dun & Bradstreet initiatives.
Key Responsibilities:
- Work on development of B2B Fraud solutions which includes Standard and custom solutions catering to various clients including fortune 500 companies
- Work with internal / external D&B clients and stakeholders; Participate in all aspects of a modelling engagement, including design, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting
- Design, develop and test new risk signals to effectively identify fraud patterns
- Serve as a Subject Matter Expert on fraud detection models within the Analytics team and with business users; consult with the business, as appropriate, on predictive modelling solutions
- Ability to manage multiple assignments, many of which with challenging timelines
- Ability to work independently, as well as collaborate effectively in a team environment
- Partner with internal D&B team to develop new business solutions in risk analytics
Key Skills
- Master’s degree or higher with concentration in a quantitative discipline such as (Math/Stat, Economics, Computer Science, Finance, Operations Research, etc.) with 5+ years of experience in Data Science.
- Proven experience on design and development of Risk models and frameworks
- Experience in design and development of Fraud models is desirable.
- Strong experience in Scorecard Development, application of Machine Learning Models using techniques such as Xgboost, Light GBM, Random Forest, Logistic Regression, Decision Tree, Neural Networks etc.,
- Strong programming skills with the ability conduct research utilizing Python and Pyspark to manipulate data and conduct statistical analysis
- Strong SQL skills and experience working with large datasets
- 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
All Dun & Bradstreet job postings can be found at https://www.dnb.com/about-us/careers-and-people/joblistings.html and https://jobs.lever.co/dnb. Official communication from Dun & Bradstreet will come from an email address ending in @dnb.com.
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Top Skills
Python
R
SQL
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