Founding Applied Data Scientist at Outtake
New York City, NY
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Jul 27, 2026
New York City, NY
Jul 29, 2026
What this job asks for AI summary
A founding data hire at an early-stage AI security startup, responsible for building the entire analytical data foundation from scratch — pipelines, semantic layers, canonical metrics, and AI evaluation systems. The role spans analytics engineering, product and business intelligence, and LLM/agent performance measurement, with an expectation to eventually hire and lead a data team. Best suited to a senior generalist who thrives in ambiguous, high-ownership startup environments.
Senior level · 5+ years · New York-Newark-Jersey City, NY-NJ-PA · Full-time
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“or” means any one of them counts — you don't need all of them.
Posted 2 times — it's one opening, so apply once.
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 240 people in the New York-Newark-Jersey City, NY-NJ-PA area plausibly meet what this posting asks for (data scientists). range 180–310
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 $138,970 (middle half $103,548–$176,968).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 29, 2026. It is a model, not a headcount.
Why we read it this way (7)
The role title is 'Founding Applied Data Scientist' but the day-to-day work spans analytics engineering (pipelines, semantic layers, dbt-style modeling), product/business BI, and AI/LLM evaluation — making it a genuine hybrid. 15-2051 Data Scientists was chosen as primary because of the explicit AI evals, model performance measurement, and applied data science framing; 15-1243 Database Architects is the runner-up given the heavy emphasis on building the analytical data infrastructure and semantic layer.
No compensation range is stated in the posting.
The role is listed as in-person 5 days a week at a Brooklyn, NY office — remote is not offered.
The 'Nice to have' section lists specific tooling (Hex, Langfuse/Braintrust/Arize/Phoenix, ClickHouse/BigQuery/Snowflake/Databricks/DuckDB, dbt, Python/TypeScript) that does not appear in the hard requirements block; all are marked preferred accordingly.
Langfuse, Braintrust, Arize, and Phoenix are listed together as interchangeable AI observability/eval tools; they are captured as a single skill with alternatives.
ClickHouse, BigQuery, Snowflake, Databricks, and DuckDB are listed together as interchangeable analytical data systems; ClickHouse is used as the primary name with the others as alternatives.
The requirements section references 'modern AI eval frameworks, model performance measurement, LLM observability, or similar systems' without naming a specific tool — this is captured as the 'LLMs' skill (hard gate on the capability) with specific tooling appearing only in the Nice to have section.
Read the full posting
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