Jamar Suárez

Jamar Suárez is a distinguished Senior Data Scientist based in P&C Global’s Madrid office, where he applies advanced quantitative finance and AI methodologies to strategic business problems. A native of the charming Castilian town of Sigüenza, Jamar brings a grounded and thoughtful perspective to his work. He serves as a core leader within the Data & Cognitive Sciences, Quantitative Analytics, Artificial Intelligence, and Machine Learning practice groups, delivering real-world impact across Manufacturing, Information & Data Sciences, Financial Services, Retail, and Travel & Hospitality sectors.

Jamar’s academic foundation reflects his deep expertise in both AI and quantitative finance. He earned his Bachelor of Science in Computer Science & Mathematics from Universidad Politécnica de Madrid (UPM) and a Master of Engineering in Logistics & Supply Chain Management, jointly awarded by the University of Zaragoza and MIT Zaragoza Logistics Center. Further he earned a Master of Science in Quantitative Finance from HEC Paris. To broaden his leadership in innovation and digital strategy, Jamar completed an Executive Certificate in Strategy & Innovation from MIT Sloan and an additional certificate in Artificial Intelligence: Implication for Business Strategy from MIT edX.

Jamar’s career reflects a strategic progression through data-driven roles at global leaders. He began his career as a Data Analyst at Siemens Spain where he built sensor-driven predictive maintenance models, reducing manufacturing unplanned downtime by 20%. As a Quantitative Risk Analyst at BBVA, he developed ML-driven credit risk assessment models, improving risk accuracy by 25%. He then advanced to Zara (Inditex) assuming the position of Senior Data Scientist where he led dynamic pricing and inventory optimization algorithms, boosting revenue per SKU by 18%. Most recently, Jamar held the position of Lead Quantitative Modeler at Iberia Airlines, where he engineered demand forecasting tools integrating dynamic macroeconomic and traveler sentiment signals, increasing load factor by 12%. At P&C Global, Jamar now leads diverse teams of data scientists, quant analysts, and ML engineers to deliver large-scale, data-driven transformations for clients across multiple sectors.

Jamar has led transformative engagements across Manufacturing, Retail, and Travel & Hospitality, applying his expertise in quantitative analytics, AI, ML, and computational finance to deliver measurable outcomes.

1. AI-Powered Predictive Maintenance for European Manufacturer
   A leading European manufacturing firm engaged Jamar to implement an AI-driven predictive maintenance system using sensor data and transformer-based failure prediction algorithms. The initiative integrated real-time equipment monitoring with advanced modeling to foresee malfunctions before they occurred.
   
   Outcomes:
   • Reduced unplanned downtime by 30–40%, aligning with industry benchmarks. 
   • Increased overall equipment effectiveness (OEE) by 20%, boosting production efficiency.
   • Lowered maintenance costs by 22% through timely, data-informed servicing.
2. Smart Inventory Optimization for Premium Retail Brand
   For a top-tier luxury retail chain, Jamar developed an AI-enhanced inventory management engine combining time-series demand forecasting, supply chain data, and machine learning optimization.
   
   Outcomes:
   • Reduced excess inventory by 20–25%, consistent with leading retail AI outcomes. 
   • Increased stock turnover by 15%, reducing cash tied in unsold goods.
   • Achieved $50M in annual savings, via optimized logistics and waste reduction.
3. Dynamic Fare Forecasting for Global Airline
   A major international airline enlisted Jamar to construct a dynamic fare and demand forecasting platform, integrating macroeconomic signals, historical ticketing data, and traveler behavior analytics powered by NLP and ML.
   
   Outcomes:
   • Improved revenue per available seat-mile (RASM) by 12%.
   • Enhanced load factor by 10%, enabling better capacity utilization.
   • Added $100M+ in incremental annual revenue, driven by algorithmic fare optimization.

Born and raised in Sigüenza, Jamar carries a strong connection to community and authenticity. Today, he lives in Madrid with his wife, Isabella, a renowned Italian chef with her own television series, and their two children. Their home is a culinary hub, where lively family dinners—mixing Spanish tradition and Italian flair—are a weekly highlight.

Moving from a quiet Castilian town to cosmopolitan Madrid with a family necessitated adaptability—and it taught him how to balance big-city life with warm family rhythms. Jamar often unwinds with his children by exploring Madrid’s street art or taking weekend trips across Andalucía to connect with Spain’s layered cultural tapestry.

Reflecting on his role at P&C Global, Jamar shares:

“I’m passionate about giving clients not just models, but clarity—turning complex data into strategies they trust. That’s why our work resonates: we empower decision-making through insight and empathy.”

With a touch of humor, he adds:

“Working here has helped me find a rhythm—like perfecting paella, data-driven work takes time, precision, and a good pinch of intuition. My colleagues say I’m the only data scientist who describes models as ‘al dente!’”

Jamar’s melding of quantitative rigor, strategic insight, cultural authenticity, and heartfelt humor make him a valued senior leader at P&C Global. Clients and colleagues alike appreciate his warm approach, deep intellect, and capacity to turn data into human stories that drive impact.