Products: behavioural data, product recommendations, product catalog data- Scaling the behavioural data tracking and pipeline for large enterprises and consumer features (daily 800M events from AWS architecture to GCP)- Crafting and leading a streamlined recommendation experience for the marketers leading to higher retention and lower operational costs.- Creating the targeted (predictive Machine Learning) AI vision and strategy of Emarsys.

- Coordinating the core data (contact list data and others) and application transition from private cloud to Google cloud infra. This meant 30 TB data with all consumption sides, to enable the opening to large enterprise customers.- Bringing SSO feature to the market (100+ customers, 1000+ users)- Introducing OAuth 2.0 for API authentication. (full GTM)

- Researched of Hungarian news' statistical relevance in macroeconomic forecasting.- Lead fintech and tech related projects: SmartMap, Innovation Hub, MNB datalake initiative.

- Growing the area to 17 colleagues, 3+ larger scale projects at a time. Creating 2 chapters (Product Owners and Engineering) based on the Spotify methodology and introducing agile culture to manage the upscale.- Shipping and maintaining several Python applications to NN units, providing solutions on risk and finance calculations and automations.- The team playing a role in technological progression of NN: moving away from manual and Excel-based processes to cloud-based applications.- I participated in the company management - NN RAS grew from 20 to 80 colleagues in Budapest and plays a significant role in providing quantitative solutions and services towards the European units.

- Founder of the Modelling & Scripting team with a mission to introduce R and Python as standard technologies on the quantitative Excel-based fields of NN Group and International units.- I lead 2 quants at first and grew the team to 6.- My main focus was on enabling the team to grow professionally and to channel in multiple projects where we can give future-proof solutions.- Among others we built an automated model surface, helping to reduce contract churn by ca. 40%. We built the Python-based cash flow model for the Dutch market-leader Non-life unit to align with the new IFRS17 regulations.

- Contributed to transform the 2 major cash flow models of the Dutch NN unit into a new framework. (80BLN EUR Liab covered)- As lead developer of automation projects in R, brought the longest taking financial reporting processes from varying old technologies into one comprehensive framework, saving significant resources (1000s of yearly working hours).

- Enhanced the testing framework of the Central European cash flow models- Researched lapse and mortality methodologies and brought them into production at several NN units.

Teaching introductory probability theory and statistics for a group of 30 software engineering students.