Who we want:
Are you committed to using your talents in research and advanced analytics to give global organizations critical advice?
Are you a leader who applies your instincts and expertise to discover breakthroughs that are key to clients’ growth?
Are you a driven professional who can manage multiple projects, set a standard of excellence and follow through on commitments for exceptional results?
Do you instinctively connect with others, understand individuals’ needs and share your passion for analytics to achieve shared goals?
Do you excel at building predictive models using various data sources and techniques to inform practical business decisions?
As a Gallup senior data scientist, you will help clients effectively use data to make better decisions. You will apply your knowledge of various statistical and machine-learning techniques to lead a wide variety of challenging projects — from designing custom client builds to automating solutions to the complicated problems clients face every day. You will partner with client teams to increase Gallup’s global impact by helping explain and predict large-scale social behavior (e.g., consumer spending, lifestyle trends, political stability, election outcomes, and employee performance and retention) using data from Gallup, the web, third parties (e.g., governments, IGOs and NGOs) and clients. You will mentor and develop other data scientists, helping them grow their technical and consulting skill sets. In short, you will be a senior leader who will help continue the development of data science at Gallup.
Gallup’s unique data give you an unparalleled opportunity to use your creativity to explore new avenues of social research. George Gallup’s legacy — founded in 1936 — established Gallup’s gold standard in survey research methodology.
What you need:
Ph.D. required. A degree from a statistics, engineering, mathematics, computer science, computational social science, physics or operations research program preferred.
Previous or current Top-Secret U.S. government clearance required
At least 16 years of work experience (which can include years spent earning advanced degrees)
Expert-level production coding in Python preferred
Mastery in conducting analysis in Python and/or R required; additional analytic software experience a plus
At least four years of experience building production-level machine learning and predictive analytics systems with data pipelines required
A deep understanding of the mathematical fundamentals of machine learning and statistics, with an emphasis on nonparametric, nonlinear methods (e.g., random forests, support vector machines, neural networks) and natural language processing required
At least one year of experience working within distributed systems and managing workflows in a cloud infrastructure required
Must be currently authorized to work in the United States on a full-time basis
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