Wersel Labs is hiring senior practitioners and engineers to build the analytics partner regulated banks and insurers will choose for the next decade. Founder-led, AI-native by design, and engineered to ship work the regulator can defend.
We were founded in 2026 to remove the legacy consulting playbook from regulated analytics — fewer pyramids, more senior practitioners, and AI-native engineering across every model we ship. The team brings together IFRS 9 credit specialists, BPA actuaries, BCBS 239 data architects and applied-AI engineers who have deployed LLMs inside live regulatory workflows.
If you have spent a career inside a Tier 1 bank, a life insurer, a syndicate or a regulator — and you want to apply that judgement at velocity, with modern tooling and a small team — we are building the firm for you.
Founding-team roles across our core practices. Levels span Senior Manager to Director / Partner — early hires shape the practice they join.
Credit risk, IFRS 9 ECL, IRB and regulatory capital practitioners with depth in retail, SME or specialist lending. You will lead engagements with Tier 1 banks, challenger lenders and private credit firms — and shape our system-wide stress, consumer-credit and affordability propositions.
Qualified actuaries (FIA / IFoA equivalent) with IFRS 17, Solvency II, Bulk Purchase Annuity or matching-adjustment experience. You will partner with chief actuaries and CFOs on capital strategy, M&A integration and the BPA pricing pipeline.
Production ML engineers who have shipped models inside regulated environments — credit, pricing, fraud, claims. Comfortable with the model-risk lifecycle: monitoring, drift, challenger models, validation. Strong Python; familiarity with cloud ML platforms.
Applied LLM engineers building retrieval pipelines, agentic workflows and evaluation harnesses for regulated workloads. Experience with prompt evaluation, hallucination control, lineage capture on prompt/response and challenger review patterns. Anthropic / OpenAI / open-weight model exposure welcome.
Senior data engineers fluent in modern warehouse stacks (Snowflake, BigQuery, Databricks), pipeline orchestration and lineage tooling. BCBS 239 or regulated-data-governance exposure is a strong plus. You will architect the data substrate under every model we ship.
Statistical modellers who have built and defended scorecards, PD/LGD, pricing engines or reserving models in front of a supervisor. You bring the quantitative craft; we pair you with AI-native tooling that compresses the documentation and validation cycle.
Headquartered in London, with engineering, actuarial and engagement teams across Asia, the Middle East and South-East Asia. We operate as one firm — embedded with clients, distributed by design.
No pyramids. The practitioner the client meets at pitch is the practitioner who ships the work.
Every pipeline, model and governance artefact is engineered with AI tooling at the core — not retrofitted afterwards.
Every model we ship is engineered to survive supervisor inspection at first review. Documentation, lineage and validation are part of the deliverable, not an afterthought.
Engagements end with your team owning the model and the tooling. Knowledge elicitation in, capability handover out.
100% founder-owned. No exit timeline pressure on the work or the team. We're building the firm we'd want to spend a career inside.
We hire on judgement and craft, not job titles. If your discipline overlaps with what we do — banking risk, actuarial, applied AI or regulated data engineering — write to us with a short note on the work you're proud of.
Write to careers@wersel.io