Requirements:

Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.

Nice to haves:

Experience delivering insights from ML to customers (e.g., problem scoping/definition, modeling, interpretation).
Experience using or deploying digital analytics and measurement solutions.
Experience in Computer Vision and NLP in the context of marketing analytics, with the ability to bring generative AI technologies to customer problems in marketing.
Knowledge of the statistical algorithms used in Marketing Analytics.

Lead data science aspects of client engagements in the area of marketing portfolio management.
Collaborate with customers to solve their problems and identify the best statistical techniques that can solve the problem, and own the development of modeling framework.
Engage important stakeholders to assess data and model readiness and be able to scale a proof-of-concept to a solution.
Work with customer and internal teams to translate data and model results into tactical and strategic insights for decision-making, and work with clients to integrate recommendations into business processes.
Collaborate with Product/Engineering teams to increase and optimize capabilities of the Applied DS team, employing methods which create opportunities for scale, and help to drive innovation.

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