Senior Data Scientist

Houzz · Israel (Remote) · posted Oct 1, 2026

Open to candidates in Israel

Full-timeseniorSaaS
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What this role actually asks for

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Must have

  • •5+ years experience with analytics
  • •Strong proficiency in SQL and Python
  • •Solid foundation in statistics and experimentation
  • •Ability to work independently
  • •Strong communication and presentation skills
  • •Practical experience working with LLMs

Nice to have

  • •Advanced degree in a technical field
  • •Understanding of US business accounting workflows
  • •Familiarity with evaluating generative AI systems

Tools and technologies

SQLPythonTableauLLMs

The full posting

About the Role

We’re seeking a high-caliber Senior Data Scientist to lead data science initiatives on the Document, Accounting, Takeoffs and Pro Commerce tracks, which are mission-critical aspects of a pro’s project lifecycle. Our mission is to be the thought partners of the Houzz Pro software product team by providing data driven insights to guide product development and business direction. You will work closely with PMs, Engineering, Design and sometimes senior leaders in this role.

What You’ll Do:

  • Be the thought partner of the PMs leading the document, accounting, takeoffs and pro commerce tracks to define key metrics, measure and derive insights on how professionals use these features and drive conversations to shape growth oriented product strategies and optimize product roadmap

  • Lead complex data science initiatives, including sophisticated analyses, independently own the design, running, and analysis A/B tests and other causal inference methods, apply machine learning methods where appropriate and drive adoption of recommendations across teams so we can deliver the best end-to-end document journey, accounting experience, etc.

  • Dig into large, complex datasets to uncover what drives value for professionals, and translate your findings into clear narratives and dashboards for stakeholders at every level

  • Work with data engineering to improve data pipelines, instrumentation, and data quality so the team can move fast with confidence

  • Use AI tools to speed up your own work, from exploratory analysis and code generation to automating recurring reporting, as well as innovative DS projects to uncover new opportunities

  • Work effectively in areas of significant ambiguity, framing hypotheses, defining success metrics, and leading the implementation of solutions to complex, open-ended problems with minimum guidance, and effectively communicate results to the entire organization including senior leaders

  • Provide technical guidance to junior team members and foster a culture of continuous learning

At a Minimum, We’d Like You to Have:

  • A B.A./B.S. degree in technical/quantitative disciplines or equivalent practical experience

  • 5+ years experience with analytics, preferably with a SaaS business

  • Strong proficiency in SQL and Python

  • A solid foundation in statistics and experimentation, including A/B test design, causal inference, and knowing when a result is truly meaningful

  • An ability to work independently, run their own projects, host stakeholder meetings, manage expectations of senior leaders and do what is needed to complete the projects with minimal supervision

  • Strong communication, presentation and interpersonal skills at senior leadership levels

  • Practical experience working with LLMs, such as calling model APIs, writing and iterating on prompts, or fine-tuning models for specific tasks

  • Excellent time management and prioritization skills to operate with high autonomy

  • A product mindset and genuine curiosity about how small businesses and home professionals work

  • Experience using Tableau

Ideally, You'll Also Have:

  • Advanced degree in a technical field such as Statistics, Operations Research or Engineering

  • Baseline understanding of US business accounting workflows or ERP integrations like QuickBooks; familiar with the home construction, remodeling, or trade business operations such as the concepts of estimating, invoicing, etc.

  • Familiarity with evaluating generative AI systems, including approaches for measuring output quality, detecting hallucinations, and using LLMs as evaluators

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