A Madrid-based investment analytics team is hiring a hands-on Quant Team Lead to combine deep mathematical modelling with day-to-day leadership of a small team.
This is not a “manager-only” job. You’ll build models, validate assumptions, work in Python + SQL, and still be the person who sets the technical standard, coaches others, and helps the team deliver decision-grade outputs under real deadlines.
Location: Madrid (Hybrid) — typically 3 days/week in-office.
What you’ll do
- Lead the analytics delivery on live valuation / portfolio analysis work (hands-on modelling + ownership).
- Mentor and level-up analysts: technical reviews, modelling best practice, quality control, and clearer communication.
- Improve quantitative models used for valuation, forecasting, and risk/sensitivity analysis.
- Turn messy datasets into reliable outputs (data QA, reconciliation, controls, repeatable pipelines).
- Run scenario analysis / stress testing and clearly explain key drivers of value and risk.
- Present your findings to senior stakeholders (committee-style conversations) and defend assumptions calmly.
- Improve how the team works: templates, documentation, automation, and model governance.
What we’re looking for (must-haves)
- Strong mathematical/quant foundation (e.g., Maths/Stats/Physics/Engineering/Quant Finance/Econometrics).
- Proven experience in quantitative finance / risk / valuation / portfolio analytics (credit risk, asset valuation, model validation, treasury/ALM, derivatives/structured products, etc.).
- Strong Python (pandas + modelling workflow) and SQL (real datasets, performance/accuracy, QA checks).
- Leadership signal: team lead/manager/project lead, or clear evidence of mentoring/coaching and quality ownership.
- Able to work at pace and produce decision-grade analysis (clear thinking, pragmatic modelling, strong judgement).
Nice to have
- Credit risk modelling exposure: PD / LGD / EAD, IFRS 9 / regulatory capital topics.
- Model validation / model risk governance experience.
- Time series, simulation (Monte Carlo), optimisation, or ML applied pragmatically.
- Experience building robust analytics tooling (pipelines, controls, dashboards).
Why this role (Madrid)
- A rare mix of serious quant depth + leadership without leaving the modelling behind.
- High-impact work where your analysis directly supports real investment decisions.
- A team environment that values mathematical rigour, clear reasoning, and strong collaboration.
Interested? Apply using the link and I will review in detail and if suitable I’ll share full details + process.
Ref: BBBH26061
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