Offer summary

Qualifications:

4 to 7 years of experience in Economics, Econometrics, Statistics, or Mathematics with a quantitative specialization., Strong programming skills in Python/Pyspark are required., Comprehensive knowledge of econometric, time series, and machine learning modeling is essential., Excellent collaboration, communication, and project management skills are necessary. .

Key responsabilities:

Develop solutions providing econometric and time series insights for public sector customer problems.

Prepare publication-quality economic reports and contribute to the automation of these reports.

Communicate analytical results effectively to business managers and senior leadership.

Participate in all aspects of modeling engagements, including design, development, and reporting.

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! Learn more at dnb.com/careers.

Overview

As an Econometrician focused on Dun & Bradstreet’s Public Sector Advanced Analytics team, you should love tackling hard problems utilizing econometric and ML approaches using large datasets. You should be willing to learn new methods and technology, while serving as an expert in your respective domain.

Key Skills

Strong Analytical and Problem-Solving Skills, Statistical Modelling, Data Analysis, Macro Economic Modeling, Machine Learning etc.,

Primary Responsibilities Include but Are Not Limited To

Help development of solutions that provide global or country-specific econometrics and time series insights that address and solve public sector customer problems.

lowing precise methodological guidelines.

Develop approaches that leverage econometric, time series and ML methods blended with economic theory covering topics including but not limited to causal inference, climate risk and spatial economics for use as products.

Preparing drafts of publication quality economic reports/commentaries/papers based on public sector data science solutions, also contribute towards scalability and automation of such reports.

Communicate analytical results in terms that are meaningful to business managers and senior leadership internally and externally.

Participate in all aspects of ongoing modeling engagements, including design, development, validation, calibration, documentation, approval, implementation, monitoring, visualization, and reporting.

Develop a working knowledge of how current systems and data sources are used in existing predictive modeling projects; drive timely retrieval of analytics data from existing system to create algorithms that meet business needs.

Requirements

4 to 7 years of experience with a degree in Economics, Econometrics, Statistics, or Mathematics, with a quantitative specialization

Programming (Python/Pyspark ) skills are required.

Comprehensive knowledge of econometric, time series and ML modeling. Hands-on experience with topics such as causal inference, climate risk modeling and spatial economics is a plus.

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.

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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