- Defined and executed the company’s overarching product and AI/data strategy in direct collaboration with C-level management, resulting in key business process improvements that adhere to 𝗰𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲 standards - Cultivated a data- and AI-literate culture across the company through ongoing workshops, resulting in a >40% increase in awareness and understanding of AI tools across departments- Built and led a coherent, high-performance team focused on AI initiatives from the ground up, driving rapid prototyping and accelerated development- Spearheaded the end-to-end development of two innovative generative AI products from concept to launch, within 3 months, each driving critical business outcomes- Led contributions to ISO 27001, ISO42001 and SOC 2 certifications and related processes adhering to these regulations, ensuring rigorous data security and compliance standards for Data and AI operations- Established a continuous discovery process with product users, which enhanced product development efficiency and satisfaction, resulting in a >20% increase in productivity- Integrated user insights throughout the product lifecycle, creating an iterative improvement framework that optimized user-centered design, boosting feature adoption rates by >30%

Consulting services in the area o Product Strategy, Product Management, Artificial Intelligence.

Led two product teams (product designers, UX designers, software engineers), handling three products===Through strategic initiatives and relentless focus on user engagement, successfully 2x the user base within 6 months of one product, for more efficient monetization for music owners===Contributed in the development of two groundbreaking products utilizing Artificial Intelligence for audio and video recognition===Increased the collaboration effectiveness between the product teams and the functional Data Science and Product/UX design teams

I designed and led the AI and HPC industry program, overseeing a portfolio of 20+ projects in AI, HPC, and Multiscale Simulations. ===I managed a data science and engineering team, delivering solutions across finance, healthcare, energy, and biotech ===I scouted over 150 companies, coordinated projects, and trained employees in AI, focusing on Natural Language Processing and Computer Vision

Led 2 cross-functional teams with total headcount of 22 (engineers, data analysts/scientists, product managers, engineering managers) under the risk domain===Ensured the delivered products/services were aligned with the company's global expansion strategy===Reduced delivery time for deploying services in new markets from 4 weeks down by 50%===Led the migration of legacy services to AWS serverless services, reducing costs and development time===Spearheaded the contractual procedures with external risk, fraud and alternative data providers in several European markets===Supported contractual procedures for external data provision in US and Australia, key markets in company's expansion strategy

Led a team of 4 data scientists in building distributed traffic analysis algorithms and extracting insights from mobile signaling data. Worked closely with sales, engineering, product and data science teams.

- Designed and developed public transportation traffic models using machine learning and network analysis- Created data products for public transit companies- Developed eveloping distributed algorithms for the company's (big) data processing pipeline

Designed, built, analyzed nanostructured devices (light emitting diodes, organic/hybrid solar cells). Worked on software that modeled light scattering and absorption. Project manager of EU project on nanotechnology applications.

Studied the electronic and structural properties at organic/graphene interfaces in multidisciplinary EU-funded Marie Curie project. My main work involved designing experiments and analyzing spectroscopic data.Worked for industry leaders for analyzing device components using spectroscopic techniques. Designed and performed experiments in synchrotron facilities in various EU countries.

Analysed correlation between deep neural signals from rodents for better modeling of Parkinson’s disease in humans. This work was done to elucidate the mechanisms of deep brain stimulation (DBS) and find new brain areas that reduce Parkinson's symptoms when stimulated.

Analysed size distribution of proteins from light scattering data and modelled phase diagram of protein solutions using absorption data

Worked on non-invasive Brain-Computer-Interfaces (BCIs) and sp atial filtering