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Data Scientist (Causal Inference & Experimentation)

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Onsite

Data Scientist (Causal Inference & Experimentation)

Harnham

Data Scientist (Causal Inference & Experimentation)

Skills

PythonProduct StrategyData ScienceData AnalysisMachine Learning

1 month ago

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Important information


Contract type:

Permanent

Location:

United States

Work mode:

Onsite

Published on:

26 September 2026

What they need


We are seeking a Data Scientist to lead the measurement, experimentation, and causal modeling work at the core of a next-generation decision intelligence platform. This is a unique opportunity to join an early-stage, venture-backed company and play a foundational role in shaping both the product and the future of the organization.

You'll work directly with founders, fellow data scientists, and customers to develop advanced causal inference models that help organizations make better business decisions from complex data. This role is ideal for someone who enjoys moving quickly, thrives in ambiguous environments, and wants significant ownership over a core product capability.

Responsibilities

  • Own the design, development, testing, and deployment of causal inference and experimentation models
  • Take research concepts and prototypes through production implementation
  • Build and improve models that power customer recommendations and decision-making
  • Validate model performance using real-world customer data
  • Design and analyze experiments to measure business impact
  • Partner directly with customers to understand use cases and communicate findings
  • Collaborate closely with founders, product leaders, and engineering teams
  • Help shape the long-term product and data science strategy

Required Qualifications

  • PhD strongly preferred; Master's degree considered in Economics, Statistics, Computer Science, Applied Mathematics, or a related quantitative field
  • 1+ years of hands-on experience applying causal inference methods in production environments
  • Experience with:
  • Difference-in-Differences (DiD)
  • Synthetic Control Methods
  • Double Machine Learning (DML)
  • Strong A/B testing and experimentation experience
  • Advanced Python skills for statistical modeling and machine learning
  • Demonstrated ability to take models from development through production deployment
  • Exceptional communication skills with both technical and non-technical audiences
  • Desire to work in a fast-paced, early-stage startup environment

Preferred Qualifications

  • Experience in product analytics, marketplace analytics, measurement science, econometrics, or experimentation-focused data science
  • Prior startup experience or experience building products, functions, or capabilities from scratch
  • Experience building data pipelines and ingestion frameworks
  • Experience working directly with customers or external stakeholders
  • Interest in product strategy and long-term product leadership opportunities

What Success Looks Like

  • Own a core modeling workstream that becomes a fundamental part of the product
  • Deliver robust causal inference solutions that drive customer outcomes
  • Help customers confidently measure the impact of their business decisions
  • Influence product direction through deep analytical expertise
  • Contribute to building a category-defining technology company from an early stage

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