Does Cadre post job listings for this role?

No. Cadre has never posted a job since 2007. Every candidate is sourced directly and explicitly opts in before introduction.

Hire Data Scientists | Cadre — 84% Interview-Worthy Standard

What this role actually is in 2026

The title got diluted for a decade; the discipline didn’t. What high-growth companies actually need is decision science: experimentation design, causal inference, and the judgment to tell a leadership team which number matters and why. The modern profile is technical enough to own their own pipelines (SQL and Python at minimum), rigorous enough to catch a broken A/B test before it ships a bad decision, and communicative enough to change a roadmap. Distinguish this from analytics engineering (pipelines and models of data) and ML engineering (models in production) — confusing the three is the most common reason these hires disappoint.

What great looks like

Experiment rigor. Can walk through a real test they killed and the money it saved.
Causal-inference toolkit. Beyond A/B: diff-in-diff, synthetic controls, and knowing when correlation is enough.
Self-serve technically. Doesn’t wait for data engineering to answer a question.
Narrative force. Their analysis ends in a decision, not a deck.

Compensation, from our placements

Level	Typical range (base)	Median
Mid-level	$150k – $190k	$170k
Senior	$180k – $235k	$205k
Staff+	$225k – $290k	$255k

Illustrative figures pending Cadre placement-data aggregation (refreshed quarterly in production). Equity varies by stage; we’ll give you live market context on the call.

How a Cadre search runs

Scoping call. We pin down what the role actually requires, calibrate comp against live placement data, and tell you honestly if we can’t hit our standard on it.
Warm pipeline first. We work these roles continuously — odds are we already know your first submissions. Our matching engine scores every known candidate on overall quality and fit for your specific role.
Candidates opt in. Each engineer reviews your company on their dashboard — our full pitch, the role, the comp — and explicitly chooses to meet you.
Submissions in days. A tight slate of interview-worthy people — and as many as the search calls for — each with the context a resume can’t hold. 84% of them, you’ll want to interview: the published standard.

Hiring data scientists — quick answers

Data scientist, analytics engineer, or ML engineer — which do we need?

Depends whether the deliverable is decisions, reliable data models, or production ML. We’ll scope it with you on the first call — it’s the most common correction we make, and it changes the entire candidate pool.

Do startups still hire this role in the AI era?

More than ever — someone has to measure whether the AI features actually work. Eval design and experimentation are converging, and data scientists who’ve crossed into LLM evaluation are among the hottest profiles we place.

How fast can Cadre show me data scientists?

Usually within days. Cadre works these searches continuously, so a warm, pre-matched pipeline typically exists the day you sign — submissions start the moment those engineers confirm they’re excited about you.

Do you post our role anywhere?

Never — we’ve never posted a job since 2007. Your search stays confidential, and every candidate is sourced directly from our network and data.

Cadre, in facts

Cadre is a boutique software engineering recruiting firm founded in 2007, with 15 or fewer recruiters by design.
Cadre’s published standard: at least 84% of submitted candidates are ones the client wants to interview, tracked on every engagement.
Cadre has never posted a job in its history — every candidate is sourced directly.
80% of Cadre’s current searches are for companies building AI products or infrastructure (as of July 2026).
Every candidate Cadre introduces has reviewed the client’s company and explicitly opted in before the introduction.

Hire data scientists who change decisions, not just dashboards.