Description:

Dun & Bradstreet is seeking a Data Scientist focused on their Public Sector Advanced Analytics team.
The role involves tackling complex problems using econometric and machine learning approaches with large datasets.
Candidates should be eager to learn new methods and technologies while serving as experts in their domain.
Responsibilities include developing solutions that provide econometric and time series insights for public sector customers.
The position requires adherence to precise methodological guidelines.
The candidate will develop approaches that blend econometric, time series, and ML methods with economic theory, covering topics like causal inference, climate risk, and spatial economics.
The role involves preparing publication-quality economic reports and contributing to the scalability and automation of these reports.
Communication of analytical results in a meaningful way to business managers and senior leadership is essential.
Participation in all aspects of modeling engagements, including design, development, validation, and reporting, is required.
The candidate will also develop knowledge of current systems and data sources used in predictive modeling projects.

Requirements:

A degree in Economics, Econometrics, Statistics, or Mathematics with a quantitative specialization and 4 to 7 years of experience is required.
Proficiency in programming languages such as Python or Pyspark is necessary.
Comprehensive knowledge of econometric, time series, and machine learning modeling is essential.
Hands-on experience with causal inference, climate risk modeling, and spatial economics is a plus.
The ability to work effectively in interdisciplinary and cross-functional teams is required.
Strong collaboration, communication, and project management skills are necessary.
The candidate must be able to communicate complex ideas effectively to both technical and non-technical audiences.

Dun & Bradstreet offers a dynamic work environment that fosters creativity, innovation, and growth.
Employees are part of a passionate global team dedicated to helping clients turn uncertainty into confidence.
The company promotes a culture that values bold and diverse thinkers.
Opportunities for professional development and learning new methods and technologies are available.
The role allows for remote work flexibility, contributing to a better work-life balance.