Manager, Data Science
Publicis GroupeAbout the role
Company Description
Both Performance Collective and PHM sit under the Publicis Media pillar, which is a collective group of agencies that specifically focus on Media advertising under the Publicis Groupe network. Within this collection of agencies as well as the broader network, we are uniquely positioned to not only deliver innovation to our clients as we partner together but also deliver the best-in-class opportunities and benefits to our employees. We deliver the atmosphere of a startup company, with the stability of having a parenting company in Publicis Groupe. As you can see, we are growing; in the past year alone, we have hired 1/3 of our current workforce. Currently, we operate out of four locations across the US which are New York, Chicago, Detroit, Philadelphia, and Los Angeles. LifeSpeed in particular will be based out of our New York office.
Job Description
Manages all phases of data analytics, (data extraction, analysis, manipulation, synthesis & interpretation, and summary) along with the development, validation, testing, and maintenance of analytic tools, models, and algorithms for client projects and operational initiatives identified by Publicis Collective. Enjoys identifying statistically significant causal relationships, is comfortable working with big data, and is fascinated by consumer behavior
Key Responsibilities:
In partnership with the Data Science Director, design and maintain the data management and analytics environment to enable industry-leading analytic solutions
Supervises department data scientists (s)
Identifies solutions to add to Publicis Collective’s advanced analytics portfolio
Provides advanced analytic support for and shares statistical rigor best practices with department analysts
Identifies optimal statistical methods and test designs for specific analytic needs
Qualifications
Bachelor's degree in statistics, mathematics, or equivalent required, with master’s degree preferred
At least 5 years of experience in statistical analysis or data mining environments such as R, Python, or equivalent
At least 3 years of supervisory experience
Expert proficiency in statistical analysis software applications such as SAS, Stata, SPSS, or equivalent
Expert proficiency in multivariate analytics, econometric modeling, Bayesian probability, and analysis of variance, with advanced knowledge of data management concepts and SQL preferred
Expert proficiency in AI powered tools such as Datarobot or equivalent
Demonstrated ability to quickly understand complex consumer behavior and businesses concepts, including financial, operational, and strategic aspects
Strong project management and prioritization skills with a demonstrated ability to execute against multiple projects and excel in a fast-paced, results-oriented work environment
Strong communication and interpersonal skills; ability to work in team environment; experience in communicating with client stakeholders and senior leadership on complex topics
Ability to work independently and manage a small team of direct reports, with guidance from the Director of Data Science
Mastery of best practices regarding sampling, multivariate methods, and tests of statistical significance
Expert ability to identify appropriate statistical procedures to address specific business or data insight challenges
Advanced knowledge of relational database concepts with ability to perform complex queries in a SQL Server environment
Additional Information
All your information will be kept confidential according to EEO guidelines.
Compensation Range: $81,500 - $128,000 annually. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. For this role, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off.
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