Data Science Manager

Data Science Manager
eCommerce
Greater New York | Remote
$145,000 - $155,000 + Bonus + Benefits

A leading consumer goods company is seeking an experienced Data Science Manager to leverage machine learning models and bayesian techniques to meet business growth.

THE ROLE:

As Data Science Manager, you will work closely with the Head of Advanced Analytics & Data Science in enhancing the eCommerce division's advanced analytics and machine learning capabilities. You will be responsible for:

• Collecting & cleaning large amounts of consumer/third-party data (i.e., website, clickstream)
• Building predictive models in Python (i.e., propensity, random forest, lookalike, regression)
• Performing A/B testing and handling existing machine learning models
• Delivering data-driven, actionable insights to a variety of key stakeholders

YOUR SKILLS & EXPERIENCE:

• Progressive Advanced Analytics & Data Science experience in eCommerce
• Strong understanding of CPG, Retail, and Consumer Health industries
• Proven experience in purchasing audiences, audience modeling, & propensity modeling
• Proficiency using advanced analytics tools like Python, R, SQL, and Tableau
• Hands-on experience in A/B testing, machine learning, and dashboarding
• Strong knowledge of random forest, time series, regression, and lookalike modeling
• Strong written/verbal communication, negotiation, and presentation skills
• Strong educational acumen - Bachelor's degree in Computer Science, Mathematics, Statistics, or related field; Master's in Business Analytics or Data Science preferred

BENEFITS:

As Data Science Manager, you can make up to $155,000 base salary (depending on your experience).

HOW TO APPLY:

Please register your interest by sending your resume to George Little via the apply link on this page.

KEYWORDS:

Propensity Modeling, Audience Modeling, Advanced Analytics, Predictive Modeling, Python, R, SQL, Tableau, A/B Testing, Random Forest, Regression, Lookalike Modeling, Machine Learning (ML), Data Science, Bayesian Techniques, Multi-Touch Attribution (MTA), XGboost, Bayes Theorem, Conditional Probability, Media Mix Model, Statistical Model