Marketing Engine Data Scientist

What You Will Own

• Build audience and target lists for priority campaigns, with clear definitions, quality assurance, and traceability.
• Deliver campaign performance readouts that translate results into actionable insights and next steps.
• Create repeatable analytics assets that reduce cycle time, improve consistency, and strengthen data quality.
• Deliver clear takeaways that explain what an analysis shows, why it matters, and what to do next.
• Use AI to work more efficiently and improve deliverable quality, applying sound judgment to validate outputs.
• Deliver a steady cadence of targeting, measurement, and insight work, including regular campaign readouts and continuous improvements to list-building and reporting processes.

Key Responsibilities

Campaign Targeting & Analysis

• Partner with digital marketing and brand teams to shape campaign ideas, define goals and success metrics, and identify target audiences.
• Build and refine target lists using data-driven segmentation and business rules and perform quality checks before release.
• Analyze campaign performance and outcomes, then recommend actions to improve targeting precision, response, and ROI.
• Create repeatable reporting and analysis assets, including notebooks, query templates, dashboard inputs, and documentation, to reduce cycle time and rework.

Stakeholder Partnership & Insight Storytelling

• Translate ambiguous requests into clear problem statements, success metrics, and analysis plans.
• Communicate findings in plain language to technical and non-technical audiences.
• Deliver stakeholder-ready summaries with key takeaways, recommended actions, expected impact, and important assumptions.
• Build trust through reliable follow-through, early risk escalation, and responsive iteration based on feedback.

Analytics & Model Development

• Contribute to segmentation and predictive analytics that support marketing strategy and customer engagement.
• Monitor analytical outputs, including models, rules, and reports, for stability and performance, and flag issues early.
• Help evaluate analytical approaches and measure impact using well-defined metrics and practical test designs.

AI-Enabled Workflow Improvement

• Use AI to accelerate analysis and improve deliverable quality, from exploratory analysis through stakeholder-ready readouts.
• Improve analytics workflows and targeting processes by reducing manual effort, increasing consistency, and improving data quality.

Technical Execution

• Use Python and SQL to extract, transform, and analyze data.
• Work with data engineering and platform partners to access curated datasets and follow established data standards.
• Follow team practices for code quality, reproducibility, and documentation, and use Git for version control.

What We're Looking For

Core Strengths

• Strong analytical thinking and attention to detail.
• Demonstrates a learning mindset, seeks feedback early, and applies it.
• Communicates effectively with stakeholders, explains results clearly, and helps align teams on next steps.
• Demonstrates ownership, follows through on commitments, and raises issues early.

Education & Experience

• Master's degree in Data Science, Computer Science, Engineering, Statistics, or a related field, with 3 years of experience in analytics, data science, or decision support; OR bachelor's degree in one of these fields, with 4 years of relevant experience.
• Commercial, marketing, or digital analytics experience is a plus. Equivalent practical experience may also be considered.
• Demonstrated ability to translate analysis into clear recommendations and practical next steps.

Technical Skills

Most work takes place in Databricks, the primary development environment for this role. Candidates should be comfortable ramping up quickly.

• Required: Python for analysis and modeling.
• Required: Strong SQL.
• Required: Foundations in statistics and measurement.
• Preferred: Databricks (primary development environment for this role).
• Preferred: PySpark and distributed data processing.
• Preferred: Git and collaborative development workflows.
• Preferred: Experience with marketing campaign analytics, segmentation, and measurement.
• Preferred: Practical experience using AI to accelerate analysis and produce stakeholder-ready readouts.

How We Work

We value end-to-end problem solving: clarifying the business question, choosing an appropriate approach, producing a sound analysis, and communicating the results clearly. Strong work concludes with a recommendation, the rationale behind it, and any important assumptions or limitations.

Physical Skills

• Parsippany based preferred
• Hybrid office setting