Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture
- doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward. You are the kind of person who thrives in a high performance/high reward culture
- doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won't find anywhere else. Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. Integral community: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package, which includes medical, dental, mental health, and vision coverage for you, your spouse/partner, and children. Client counterparts span a wide range of audiences and functions from treasury and risk professionals, marketing & sales teams, procurement category managers, to high-level stakeholders (e.g., Your work on the team will primarily be in applying advanced analytics to enable better commodity risk management decisions. For example, you might work as the lead in maintaining and expanding existing hedging strategies by re-training existing models through process driven approaches. You might also modify and improve algorithm performance across market regimes, by introducing new features, data sources,



and modelling approaches; rapidly identify opportunities for our clients to increase earnings potential and reduce downside risk by back testing various risk management strategies; co-build bespoke tools with client data science teams that tailor machine-learning algorithms to attain an optimal balance of earnings and volatility given clients' risk appetite and capital constraints; You will receive best-in-class training in structuring business problems and serving as a client adviser and have opportunities to work closely with and learn from our senior commodity and risk practitioners, as well as industry players that are shaping the future of commodity markets and trading. Lastly, you will be able to provide direct and measurable impact to some of the largest organizations in agribusiness, materials, energy, industrial, and consumer foods sectors around the globe. You'll work closely with McKinsey's Commodity Trading Service Line to support clients across sectors and geographies. Commodity Analytics helps commodity producers, processors, buyers, and traders across agriculture/softs, metals, energy, and consumer sectors improve commodity price risk capabilities with cutting-edge data science. The Commodity Trading Service Line at McKinsey supports clients in commodity trading and risk strategy, trading operations transformation,



and trading and risk digitization driven by deep trading experts with hands-on trading experience and advanced analytics assets. Undergraduate degree Production-quality Python for model development, including optimization, time series forecasting, feature engineering, backtesting, and evaluation using standard DS toolkits (e.g., pandas, scikit-learn, statsmodels, gradient boosting, etc.) Familiarity with pytest and reproducible research workflow; experience operationalizing models: versioned experiments, CI/CD, model monitoring and drift detection, and collaboration with engineering on APIs and model/solution design Ability to explain commodity market nuances and/or complex analytics approaches and results in layman's terms to executive audiences across commodity trading, operations, supply chain / logistics, and finance / accounting functions Advanced degree in a quantitative discipline (computer science, applied mathematics, economics, quantitative finance, engineering) or equivalent practitioner experience 2+ years' experience in commodity markets developing market research, trading, or hedging/risk management strategies such as netback/deal economics, signal backtesting, stress testing, and/or hedge effectiveness 2+ years' experience in physical/cash markets of metals, power/electricity markets, natural gas, crude oil, refined products, and/or ocean freight Experience integrating data science and/or automation workflows with CTRM/ETRM systems via API Experience automating middle/back-office processes with PRA and LLMs (e.g., pre-trade KYC/credit, trade execution, compliance, logistics, trade settlement) #

📌 Senior Data Scientist (España)
🏢 Mckinsey
📍 España