Salary
Posted
Jul 28, 2026
Location
Last confirmed open
Jul 29, 2026

What this job asks for AI summary

A senior, highly autonomous data scientist joining a small in-house engineering team at a crypto/AI startup accelerator in New York City. The role spans the full stack of data work — building predictive models, writing production Python pipelines, authoring SQL reports and dashboards, and integrating LLMs for research and enrichment — all the way from raw data to deployed product. Best suited to a self-directed generalist who can own ambiguous problems end-to-end without a dedicated data platform or PM support.

Senior level · New York-Newark-Jersey City, NY-NJ-PA · Full-time

Quick apply — this platform usually takes a CV and a few fields.

Must have (5)
PythonSQLMetabaseLLMsdata pipelines
Nice to have (3)
LLM evaluation systemsstructured extraction pipelinesopen-source contributions

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 590 people in the New York-Newark-Jersey City, NY-NJ-PA area plausibly meet what this posting asks for (data scientists). range 310–770

Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.

What won't set you apart
Python88%SQL72%data pipelines40%

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)

No compensation range is stated anywhere in the posting.

The posting lists no minimum years of experience; seniority is inferred from the 'Senior, self-directed' framing and the scope of ownership expected.

Metabase is named in the requirements section as a specific tool alongside notebooks, application code, and APIs — treated as a hard gate despite being a single BI tool.

LLMs appear in the requirements section ('comfortable using modern AI tools and LLMs') and are treated as a hard gate; LLM evaluation systems and structured extraction pipelines appear only under the 'good to have but not required' section.

The role is explicitly onsite-only in NYC; relocation is described as non-negotiable.

An alt SOC of 15-2031 (Operations Research Analysts) is noted because the role has a significant analytics/reporting dimension, but the modeling, ML, and AI-tool emphasis makes 15-2051 the stronger fit.

Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): predictive modeling.

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