Job Description: Data Scientist
Position Overview
Dun & Bradstreet is seeking a Data Scientist to join their Data & Analytics team. In this role, you will be involved in all facets of modeling engagements, from initial design and development to validation, calibration, documentation, approval, implementation, monitoring, and reporting. You will be responsible for researching complex business issues and proposing solutions, including model features, end products, and necessary data to support Dun & Bradstreet's growing initiatives.
- Employment Type: Employee: Full Time
- Company: Dun & Bradstreet
- Location Type: Not specified
Requirements
- Education: Master’s Degree or Ph.D. in a quantitative/applied field is preferred (e.g., Statistics, Econometrics, Computer Science, Operations Research, Mathematics, Engineering).
- Experience: A minimum of 7 years of successful experience in data science roles, particularly those involving cross-company collaboration and communication.
- Skills:
- Proficiency in utilizing the latest data science techniques, including supervised and unsupervised machine learning methodologies, Natural Language Processing, and graph analysis.
- Strong communication skills with the ability to clearly explain complex concepts to stakeholders, clients, and senior leadership.
- Proven ability to establish and maintain robust relationships with key business stakeholders.
- Experience engaging with clients and D&B colleagues to identify business needs and subsequently develop, implement, and manage solutions.
Responsibilities
- Modeling Engagement: Participate in all aspects of a modeling engagement, including design, data requirements, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting.
- Data Science Techniques: Apply data science techniques such as supervised and unsupervised machine learning, Natural Language Processing, and graph analysis.
- Business Solutions: Develop Global Analytic Solutions, including statistical models, adhering to D&B’s established best practices, methodologies, and tools.
- Research & Recommendations: Research complex business issues and recommend solutions, including model inputs and end products, with a focus on addressing specific customer needs and use cases.
- Subject Matter Expertise: Act as a Subject Matter Expert on predictive models for the team and business users, consulting with the business on predictive modeling solutions as needed.
- Knowledge Sharing: Stay current with and share academic literature and industry best practices. Identify the business relevance of new methods and collaborate with cross-functional teams to create prototypes, assist in developing business cases, and define go-to-market strategies.
- Model Validation: Validate the performance of existing quantitative risk models and propose necessary changes.
- Data Retrieval: Drive the timely retrieval of risk analytics data from existing systems to create algorithms that effectively meet business needs.
Application Instructions
Company Information
- Company: Dun & Bradstreet
- Mission: Dun & Bradstreet unlocks the power of data through analytics, creating a better tomorrow.
- Website: dnb.com/careers