Data Scientist (3-5 years experience)
Germantown, MD /
Analytical Services – Data Science /
Full-time
DataLab USA™ is an analytics and technology driven database marketing consultancy. We combine sophisticated technology, cutting edge analytics and an intrinsic understanding of marketing to build large-scale addressable marketing programs for Fortune 500 companies. Our clients operate in multiple verticals: Financial Services, Insurance, Telcom, and Travel & Leisure.
Because of our success, we are growing at a rapid pace. We have placed in the INC 5000 list of fastest growing private companies for four times in the last ten years. At its heart, DataLab USA™ has the entrepreneurial spirit of a start-up. We judge ourselves on our ability to innovate, drive efficiency and deliver excellence for our clients.
Key responsibilities/duties include:
· Build, implement and maintain predictive models through their full lifecycle.
· Identify patterns & trends in data, and provides insights to enhance business decision making.
· Identify challenges and opportunities from client strategy discussions and taking ownership of solution.
· Set up and monitor monthly model recalibration process.
· Generate complex ad-hoc analyses combining disparate concepts or creating new approaches.
· Design and create new analytic procedures & automation.
· Review corporate model scoring QC.
· Review corporate data transformation QC.
Education and Experience:
· MS/PHD in a quantitative discipline or BS in a quantitative discipline with commensurate experience
· Regular SQL use for querying data
· Experience programming with at least one language
· Use of statistical software (e.g., R, Python)
· Experience with Tableau (or other data visualization platform)
· Experience with Excel
· Financial or insurance industry experience strongly preferred
· 3-5 years of Database Marketing and Data Mining experience
DataLab USA™ is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or national origin.
