Senior Data Scientist — Ai Evaluation

About Finom Finom is a European tech startup headquartered in Amsterdam, and we're on a journey towards revolutionizing the financial landscape for entrepreneurs worldwide.
Our mission is to develop an all-in-one financial B2B solution that integrates banking functions, accounting, financial management, and invoicing into a seamless, mobile-first platform.
We recently closed a €115 million Series C equity round (around $133 million), bringing our total funding to approximately $346 million.
This significant investment follows a $105 million growth funding round from General Catalyst, a long-term backer since ***
* known for supporting companies like Airbnb, HubSpot, KAYAK, and Stripe.
Finom's platform goes beyond traditional banking, offering invoicing and a growing suite of features, including AI-enabled accounting, aiming to simplify financial management for entrepreneurs.
We're actively expanding our reach across key EU markets like Germany, France, the Netherlands, Italy, and Spain.
At Finom, we're not just redefining the entrepreneurial experience — we're empowering our employees to make a real difference.
Your work matters, and your impact extends far beyond product metrics.
We nurture innovation and an inspiring work environment where bold ideas thrive, prioritizing thorough research, swift implementation of solutions, and ensuring that every effort we make benefits our users, employees, partners, and our business as a whole.
Maintaining our start-up spirit, we prioritize thorough research, swift implementation of solutions, and ensuring that every effort we make benefits our users, employees, partners, and, of course, our business.
AI Team You'll join Finom's AI Team as the founding IC dedicated to the quality, evaluation and telemetry of AI agents powering Finom's internal operations and tools (including Ops workflows and internal AI analytics engines across ~20 core processes).
Our belief An AI agent is only as good as the evaluation loop running on it.
Because internal operational agents directly touch financial, compliance and support workflows, evaluation is an exact statistical and engineering discipline here.
Your mission Design the evaluation methodology, build golden benchmarks, and establish quality gates for our internal AI agents from scratch—working directly with process owners and domain experts, with no senior quality owner above you to lean on.
Core Stack Databricks, DeepEval, Claude Code, Cursor, Python, SQL, dbt.
What You Will Be Doing Own and extend our offline/online evaluation suites across ~20 internal AI agent processes—datasets (capability + regression), LLM-as-a-judge rubrics, and deterministic checks.
Establish pre-launch quality gates: enforce pass/fail thresholds in CI/CD pipelines before agent prompt, context, or tool changes hit production.
Work directly with domain experts to label cases and resolve annotator disagreement—fixing definition criteria rather than averaging disagreement away.
Build test datasets derived from real user & operational traffic (tickets, internal chats, colleague queries) rather than synthetic edge cases.
Harden statistical methodology: handle judge drift, verbosity bias, non-determinism, and measure true metric shifts vs. noise.
Translate quality numbers into operational decisions: run weekly syncs with process owners to define clear quality vs. cost/latency trade-offs.
Must-Haves 5+ years in Data Science / Product Analytics / Applied AI roles, with sustained product-level metric ownership.
Production LLM

Experience:
In the last 1–2 years, you have built, shipped, or evaluated LLM-based systems (RAG, multi-step tool use, agents) as a core, primary job responsibility.
Autonomous Quality Ownership: Proven track record of owning evaluation methodology or analytics for an entire product or end-to-end process (what to build vs. what NOT to build).
Fluent Python & SQL: Ability to write clean data pipelines, evaluation harnesses, and dbt transformation models directly.
Statistical Rigor: Applied knowledge of sampling, hypothesis testing, variance analysis, and confidence intervals on noisy metrics.
Daily Setup & Tooling AI-assisted coding (Claude Code, Cursor, or Codex) is your default daily authoring environment for Python, SQL, and evaluation scripts—not something you occasionally experiment with.
You can walk us through concrete work tasks from the last month where AI coding tools accelerated your engineering and data analysis.
How we work — one thing we mean seriously AI-assisted coding is our default authoring environment, not a bonusClaude Code is our main tool — you'll reach for it for SQL, Python, analyses, dashboards, and internal scriptsWe're looking for analysts who are already curious and fluent with AI coding — or genuinely excited to become fluent fastWe care about what you ship and how clearly you thinkIf this idea excites you rather than worries you, you'll feel at home hereWhat You Will Get In Return Make a genuine impa