Senior Manager, Data Science - Public Sector (R-18193)
Arlington - Virginia - United States
Dun & Bradstreet
Meet sales and marketing goals, navigate global supply chains, and mitigate credit risk with nearly two centuries of D&B business data and analytics expertiseAs a people manager and data science econometrician focused on Dun and Bradstreet’s Public Sector team, you should love tackling hard problems utilizing Gen AI, Machine Learning, and econometric approaches using large datasets.
The Senior Manager, Data Science - Public Sector will be enthusiastic to learn new methods and technology and directly mentor others in the career.
The Senior Manager, Data Science - Public Sector will serve as an expert in your respective domain, learn from others skilled in other domains, and train and support individuals in developing technical expertise to solve business and policy relevant problems.
Key Responsibilities:
- Lead the development of solutions that use Generative AI, vector search, classification and geo-spatial methods and drive innovation and adoption in these areas.
- Develop approaches that leverage econometric, sampling, time series and ML (including deep learning) methods blended with economic theory covering topics including but not limited to causal inference and spatial economics for use as products.
- Prepare drafts of publication quality economic reports/commentaries/papers/presentations based on public sector data science solutions, and lead and participate in drafting RFIs and RFPs on topics of specialization.
- Communicate analytical results in terms that are meaningful to business managers and senior leadership internally and externally.
- Lead and participate in all aspects of ongoing modeling engagements, including stakeholder management, design, development, validation, calibration, documentation, approval, implementation, monitoring, visualization, and reporting.
- Serve as an advisor to members of your team and empower individuals to take ownership of their projects delivering on-time and meeting business requirements.
- Develop and train individuals to have working knowledge of how current systems and data sources are used in existing AI (e.g., generative and causal) related and other projects; drive timely retrieval of analytics data from existing system to create algorithms that meet business needs.
Required skills:
- 5 to 10 years of experience with a degree in Economics, Econometrics, Statistics, Mathematics, or Computer Science with a quantitative specialization.
- Programming (Python/Pyspark, SQL, Linux/command line) skills are required.
- Ability to work with GPUs, VMs, and data science tools like Jira, Git, Confluence strongly preferred.
- Lead projects involving large-scale unstructured data using Generative AI and vector search methods to extract insights and drive innovation.
- Keep up with and lead working sessions with data scientists and econometricians on the new developments in Generative AI, agentic approaches to problem-solving, and their practical implementation in code.
- Ability to work on an interdisciplinary and cross-functional team.
- Strong collaboration and communication abilities (including writing) and project management skills.
- Ability to effectively communicate complex ideas to both a technical and non-technical audience.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Causal inference Classification Computer Science Confluence Deep Learning Econometrics Economics Generative AI Git Jira Linux Machine Learning Mathematics Privacy PySpark Python R SQL Statistics Unstructured data
Perks/benefits: Career development Flex vacation Health care Insurance Medical leave Parental leave
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