Piotr Łączkowski

– Driving the company's AI disruption by leading a high-performing team of data scientists to unlock business value, elevate customer experience, and embed a data-first mindset across all functions. – Spearheading the adoption of cutting-edge AI and GenAI technologies, reimagining business processes, and guiding the enterprise through a transformative digital journey in the fast-evolving retail landscape.

– Managing big team of data scientists to improve overall business impact, improve customers satisfaction, promoting data driven approach, new technologies and leading digital and AI/GenAI related enterprise transformation in this challenging world of the retail.

– Lead Senior Data Scientist responsible for Pricing platform and Image Recognition technology for the marketplace.

– Head of Machine Learning and Artificial Intelligence development for business intelligence (Supervised, Unsupervised Learning and Deep Learning, predictions, chatbot, translations systems, recommendation systems). – Data visualization and modeling, advanced algorithm engineering for e-commerce platforms. – Code development and optimization, advanced interactive visualizations and reporting. – Technology: Django, Python 2, Python 3, Angularjs, HTML, jquery, git, gitlab, jira, AWS, S3 + all data science kit (tensorflow, Keras, sklearn, numpy, pandas, scipy, mpl, Seaborn), Tableau, Alteryx, Vertica, MySQL, Snowflake, Snowplow, Docker, Linux, PySpark...

– Worked in an international team of scientists led by a Nobel Prize winner: Albert Fert. – Signal and Data acquisition (Labview, Matlab, Python, GPIB, MPL, GUI Design), Data Analysis, processing and modeling (ML - classification algorithms, FEM, parallel cluster calculations). nanodevices and nanofabrication (transistors, memristors, skyrmions and domain wall tracks, bio-inspired computing). Data visualization, project management.

– Spintronics and Nanofabrication. – Data acquisition, analysis, modelling and visualisation (Python, FEM, parallel computing, PyQT-GUI), advanced algorithms development. – Regression, fitting, classification, gradient descent and grid search.

– Engineering for near-field microscopy: type-Il superconductors. – Software design (C++, Python, Labview) and hardware fabrication (electronic circuits, filters, etc.)

– Study of magnetic vortexes in non-conventional superconducting materials (heavy fermions) using a u-SQUID scanning probe microscope mounted on a dilution cryostat.