Data Scientist

🕒 December 16, 2025

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Hightouch

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2020

☁️ SaaS

Marketing • Advertising • SaaS

Hightouch is a Composable Customer Data Platform (CDP) that enables marketing teams to personalize and optimize campaigns using customer data and AI decisioning. Built on your data warehouse, Hightouch allows for real-time personalization, audience segmentation, and journey orchestration without writing code. It integrates with over 200 tools, turning data infrastructure into actionable insights for marketing, advertising, and data teams. Hightouch empowers organizations to maintain control over their data while offering advanced features like audience targeting and conversion tracking to enhance advertising reach and campaign performance.

📋 Description

• Own diagnostics, insights, and tuning for AI Decisioning campaigns • Explain why AI Decisioning is driving lift using counterfactuals, incrementality breakdowns, and cohort analysis. • Debug performance issues, iterate on reward functions, and ensure the agent’s recommendations align with customer goals. • Investigate experiment setups (send volumes, reachability, channel constraints) and surface actionable recommendations. • Work deeply with data in notebooks and customer warehouses • Pull down historical data to run exploratory analyses using Polars / Pandas in Jupyter notebooks • Modify and improve customer feature matrices to unlock deep personalization. • Conduct deeper warehouse-level SQL analyses when insights aren’t available in the UI. • Build lightweight tooling that enables scale • Create templates, notebooks, scripts, and repeatable workflows that improve how we analyze performance across customers. • Identify systemic gaps and influence the direction of ML reporting and introspection. • Communicate ML concepts clearly to non-technical stakeholders • Present model insights and recommendations to marketers, analysts, and executives. • Explain how the decision engine handles cold start, message transfer learning, exploration vs. exploitation, and more. • Partner closely with Solutions Consultants to identify and drive new opportunities for uplift.

🎯 Requirements

• Strong ability to perform deep exploratory data analysis in Python (Polars / Pandas, Jupyter notebooks). • Ability to write and interpret SQL for customer warehouse analysis. • High-level understanding of ML modeling concepts (features, hyperparameters, reward functions, training windows). • Excellent communication skills; able to explain technical reasoning simply and confidently to marketers. • A customer-first attitude with high ownership and urgency when resolving issues. • Bonus Points: • Experience setting up and analyzing marketing experiments such as A/B, multivariate tests. • Prior experience in an applied ML, data science, analytics engineering, or forward-deployed role. • Experience building lightweight internal tools or scripting solutions.