Staff Data Scientist - Experimentation & Causal Inference at HighLevel
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Jul 19, 2026
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Jul 21, 2026
What this job asks for AI summary
A founding individual contributor role focused on building and owning the company-wide experimentation and causal inference practice for a large-scale SaaS platform. The work centers on defining end-to-end experiment methodology, applying rigorous statistical and causal inference techniques in small-sample and multi-product contexts, running concurrent experiment governance, and upskilling PMs and analysts. Suits a senior applied statistician with deep hands-on A/B testing and causal inference experience.
Staff level · 9+ years · Remote · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 4,650 people nationally plausibly meet what this posting asks for (data scientists). range 1,950–7,000
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $122,874 (middle half $87,544–$162,374).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (8)
The posting explicitly titles this role 'Staff Data Scientist', and the scope — setting company-wide experimentation standards, cross-functional influence, and a path to build out a Data Science team — genuinely supports Staff-level classification.
Python and R are listed as alternatives: the JD requires 'working proficiency in Python or R', so either satisfies the requirement.
Statsig appears only under 'Nice to Have' as an example of a modern experimentation platform.
No compensation range is disclosed anywhere in the posting.
The JD describes a founding IC role with executive sponsorship; while a future team-building path is mentioned, the role is explicitly an individual contributor (IC) position, so 15-2051 (Data Scientists) is preferred over 11-3021 (Computer and Information Systems Managers).
Several methodologies named in the JD (diff-in-diff, instrumental variables, synthetic control, CUPED, sequential testing, multiple comparisons, variance reduction) are statistical techniques rather than named tools and are therefore captured under the broader required skills rather than emitted as separate skill entries.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): power analysis.
Caller marked this a fully-remote role — scored against the national candidate pool.
Read the full posting
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