Quant Team Lead

A Madrid-based investment analytics team is hiring ahands-on Quant Team Leadto combinedeep mathematical modellingwithday-to-day leadershipof a small team.

Si le interesa solicitar este empleo, por favor, asegúrese de cumplir los siguientes requisitos que se enumeran a continuación.

This is not a “manager-only” job. You’llbuild models, validate assumptions, work in Python + SQL, and still be the person whosets the technical standard, coaches others, and helps the team deliver decision‑grade outputs under real deadlines.

Location:Madrid (Hybrid) — typically3 days/week in-office.

What you’ll do

• 
  
• Lead the analytics deliveryon live valuation / portfolio analysis work (hands‑on modelling + ownership).
  
• Mentor and level‑upanalysts: technical reviews, modelling best practice, quality control, and clearer communication.
  
• Improvequantitative modelsused for valuation, forecasting, and risk/sensitivity analysis.
  
• Turnmessy datasetsinto reliable outputs (data QA, reconciliation, controls, repeatable pipelines).
  
• Runscenario analysis / stress testingand 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)

• 
  
• Strongmathematical/quant foundation(e.g., Maths/Stats/Physics/Engineering/Quant Finance/Econometrics).
  
• Proven experience inquantitative finance / risk / valuation / portfolio analytics(credit risk, asset valuation, model validation, treasury/ALM, derivatives/structured products, etc.).
  
• StrongPython(pandas + modelling workflow) andSQL(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 producedecision‑gradeanalysis (clear thinking, pragmatic modelling, strong judgement).
  

Nice to have

• 
  
• Credit risk modelling exposure:PD / LGD / EAD, IFRS 9 / regulatory capital topics.
  
• Model validation / model riskgovernance 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 ofserious quant depth + leadershipwithout leaving the modelling behind.
  
• High-impact work where your analysis directly supports real investment decisions. xcskxlj
  
• A team environment that valuesmathematical rigour, clear reasoning, and strong collaboration.
  

Ref: BBBH26061

#J-18808-Ljbffr