Marketing Science Director

  • Location

    Detroit

  • Sector:

  • Job type:

    Temporary

  • Salary:

    Negotiable

  • Contact:

    Mike Hayes

  • Contact email:

    m.hayes@ioassociates.com

  • Job ref:

    BBBH164305_1752606940

  • Consultant:

    Michael Hayes

Director of Marketing Science

Detroit (HYBRID)

FTE

US Citizenship/Green card required

We're looking for someone to lead data-driven marketing strategies, optimize campaigns using AI/ML, and drive automation to improve results. If you're ready to make a real impact, apply now!

Responsibilities

  • Lead the development and execution of data and analytics strategies aligned with organizational goals, enhancing marketing effectiveness.
  • Manage cross-functional teams to create customer segmentation models and optimize marketing ROI through campaign analysis.
  • Act as a liaison between data teams and marketing stakeholders, translating technical insights into actionable business strategies.
  • Drive innovation by implementing automation solutions and testing frameworks to enhance customer experience and operational efficiency.
  • Foster a collaborative environment, mentoring and managing a team of Data Scientists and Engineers to deliver strategic insights and innovative solutions.

Requirements:

  • Possess a Master's degree in a quantitative field (Statistics, Data Science, Computer Science, etc.) and 10+ years of experience in data science or analytics.
  • Demonstrated leadership in data science with a focus on innovative marketing strategies, including direct mail and digital marketing analytics.
  • Expertise in predictive modeling, experimental design (A/B testing), and using advanced AI/ML techniques like Generative AI for marketing optimization.
  • Proficient in Python, SQL, and marketing platforms (DataRobot, Adobe Campaigns, DataBricks, AWS, Azure, GCP) with strong skills in data visualization tools (Tableau, Power BI).
  • Skilled in automation technologies (RPA, AI-driven workflows) and advanced statistical methods (non-parametric, Bayesian) for small sample inference and marketing insights.