AI-Led Business Growth & Revenue Impact

• Designed and deployed AI-poweredrecommendation and biddingengines at sennder, leading to a 3X increase in TGP, reaching €8M.

• Led MLOps and data platform refactoring projects across three companies, reducing OPEX by 10% in two and enabling key bottom-line gains in another.

• Developed AI frameworks for real-time intelligent pricing and routing (transportation) and risk prediction (fintech), increasing total gross margin (TGM) by up to 30%.

• Steered the design of a new affordability estimation engine at Kreditech and integrated an AI-based fraud detection module, reducing default rates by 5% and increasing revenues by 30%.

Scaling AI & Engineering Teams

• Managed more than 50 FTEs, hiring more than 30, including Ph.D. researchers and industry experts from Amazon, Meta, Apple, Expedia, Olx, Delivery Hero, and Zalando.

• Built AI and data departments from scratch in two organizations, growing them to 7 and 18 FTEs, respectively, with a fully remote, Agile-first setup.

• Championed career growth, leading to 15+ promotions and industry recognitions for direct reports.

Operational Excellence & Efficiency Gains

An example from sennder:

• AI platform refactoring at led to:

  • +70% development speed;

  • -80% production incidents;

  • -60% downtime;

• Reduced firefighting time through Shift Left in ML engineering, introducing unit tests for software, data, infrastructure, and model logic, leading to a 13% reduction in Change Failure Rate (CFR).

• Introduced pair programming for 40% of tasks, reducing knowledge silos and decreasing lead time for changes (LTFC) by 70%.

• Published 50+ high-impact AI/ML papers in top-tier venues, including KDD, AAAI, IEEE TKDE, and ECML/PKDD.

• Delivered 20+ keynote talks worldwide, from Brisbane (Australia) to Las Palmas (Spain).

• Won multiple industry awards, including a Test-of-Time Award for best paper in a world-class data mining journal (IEEE Transactions on Intelligent Transportation Systems). goes here

• AI & Machine Learning: GenAI, LLMs (fine-tuning & prompt engineering), NLP, dynamic pricing, fraud detection, credit risk, affordability prediction.

• MLOps & Data Platforms: Feature stores, DataOps, experiment tracking, model deployment, live/offline testing, serving, and monitoring.

• Data Strategy & Governance: Policy, quality, acquisition, architecture, data warehousing (OLAP), ML services (OLTP), EdgeML/IoT.

• Tech Stack: AWS (Redshift, ECS/EKS, Lambda), Python, PostgreSQL, Snowflake, W&B, Flyte, BentoML, MongoDB, Redis, Kafka, RESTful APIs (FastAPI, Flask), Kubernetes, R, C++.

• Leadership & Product Strategy: AI-driven product development, OKRs, Agile, data product management.

• Business Communication & Stakeholder Management: Strong ability to bridge technical concepts with C-level executives, VC boards, and global stakeholders, ensuring alignment and buy-in for large-scale AI transformations.