Business & Marketing Data Scientist; III

Overview

We are seeking a highly analytical and business-savvy Marketing Data Scientist to join our team. In this role, you will leverage advanced analytics, statistical modeling, and machine learning to uncover insights, optimize marketing campaigns, and drive data-informed decision-making. You will work closely with marketing, product, and sales teams to measure performance, predict customer behavior, and improve return on investment (ROI).

• Data Analysis & Insights:
  Collect, clean, and analyze large-scale marketing and customer datasets. Identify trends, customer segments, and behavioral patterns that inform marketing strategies. Translate complex data into actionable insights for business stakeholders.
• Modeling & Forecasting:
  Develop predictive and propensity models (e.g., customer acquisition, churn, lifetime value). Use machine learning and statistical techniques to optimize campaign targeting and personalization. Build marketing mix models (MMM) and attribution frameworks to assess channel effectiveness.
• Experimentation & Measurement:
  Design and analyze A/B tests and multi-variant experiments to measure campaign impact. Establish KPIs, dashboards, and reporting frameworks to monitor marketing performance. Partner with marketing teams to measure ROI of campaigns and initiatives.
• Collaboration & Strategy:
  Work cross-functionally with marketing, product, data engineering, and finance teams. Present findings and recommendations to senior stakeholders in clear, compelling narratives. Provide data-driven support for go-to-market strategies, budget allocation, and customer engagement initiatives.

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Economics, Marketing Analytics, or related field.
• 3–5+ years of experience in data science, marketing analytics, or a similar role.
• Strong proficiency in SQL and programming languages such as Python or R.
• Experience with data visualization tools (e.g., Tableau, Looker, Power BI).
• Solid understanding of marketing principles, digital advertising, and customer lifecycle management.
• Hands-on experience with machine learning frameworks and libraries (e.g., scikit-learn, Tensor Flow, PyTorch).
• Strong communication skills with the ability to simplify complex data into clear business insights.
• Familiarity with cloud data platforms (e.g., Google Big Query, AWS Redshift, Snowflake) is a plus.

• Experience with marketing attribution models, MMM, or incrementality testing.
• Knowledge of web analytics tools (e.g., Google Analytics, Adobe Analytics).
• Familiarity with CRM and marketing automation platforms (e.g., Salesforce, Hub Spot, Marketo).
• Previous experience in a tech, e-commerce, or advertising environment.