Elliot Trabac

2025 focus ➡️ Empower self-service agentic analytics, enabling the team to focus on delivering proactive insights and operations 🏔️

Leading the Data & Analytics Engineering team 🚀

Build our next-gen Data Platform that will support our mission: Delivering accurate and accessible assets at scale to empower all end data users 🚀

Gorgias provides an integrated helpdesk for e-commerce brands, making it easy to deliver personalized support and automation across multiple channels. Connect all your business and social apps, and turn customer support into a revenue generating activity! We currently serve over 5,000 businesses including Timbuk2, Steve Madden and MVMT. -- Hired to scale and support GTM initiatives using software and data 🤖

Lucis (YC X25) turns regular blood tests into actionable health insights - so people can act before it’s too late. 🧠 Advisory: AI Engineering

Join Lion teaches innovative methodologies and mindset from the startup ecosystem to startup employees as well as large enterprises. Classes and workshops: Tracking, Data and Analytics.

Helps companies grow by scaling their use of data 📈 Short & mid-term missions in Data & Analytics Engineering: - End-to-end data stack implementation/migration - Development of custom ETL connectors - Infrastructure design - Strategy

High level athlete within the Scott SR Suntour Enduro Team, I practice Enduro MountainBike since 2013 with the international races in the target. In constant progress, I invest myself daily in this sport in the quest for pleasure and performance. We are accompanied by major brands of the sport who actively participate in the success of the team. • Physical, technical and mental challenge • Communication on social networks • Product development and improvement with sponsors • International travel and sports culture Main results: • French Vice-Champion Elite 2019 • World Cup Top 15 Elite • French Cup victories and podiums Elite (from 2016 to 2019) • 3rd of the overall ranking of the U21 World Cup 2015 • World Cup podiums U21 (2015-2016)

Chance is a PsyTech pioneer - central to the emergent field of human choice facilitated by machine intelligence. We democratize the most advanced techniques and tools of coaching, profiling, and behavioural psychology usually reserved only for top executives, to make them available for all. Data & Analytics Engineering stuff 🛠 Long story short: Benchmark, set up, and maintain a Modern Data Stack (Segment, Stitch/Airbyte, PSQL, dbt, Metabase, Hightouch, downstream tool automations, alerting) + own company analytics (BI, reports, monitoring). Deeply invested in the data community and the rise of the Modern Data Stack. If you have any questions about these challenges, feel free to reach out!

Data Scientist part-time at U-Care - Medical device start-up that is developing a new diagnostic tool to predict kidney failures. Extraction and transformation of a new dataset to challenge an existing Deep Learning Algorithm 📃 • Extraction of large data volume with distributed computing technologies • Preprocessing to format the dataset to fit the model requirements • DL modeling, testing, and predictions (time series 1D-CNN, ResNet) • Model performances analysis and conclusions Stack: PySpark/Spark, Python data stack (pandas, numpy, scipy, matplotlib, seaborn..), scikit-learn, TensorFlow/Keras, Jupyter Notebook, Spyder, Colab (IDE).

Analysis and numerical modeling of multiphysical systems - AI/ML - Software engineering - Optimization and statistics - Applied mathematics - Project management - Entrepreneurship - Humanities and social sciences. ➡️ But to be honest, I spent most of my time doing business at the Junior-Enterprise or upskilling myself on e-learning platforms. A curriculum designed to combine sport, study and entrepreneurship

📃 DL project - 3months: Domain adaptive visual object detection using a different pixel-level adaptation strategy (AdaIN & CycleGAN w/ PyTorch). 📃 End-to-end ML project - 3months: Data Collection; Exploratory Data Analysis; Data Cleaning/Preprocessing/Feature Selection/Feature Engineering; Model building/Model Selection/Optimisation; Model deployment; Documentation. + Academic courses: • Data Spaces (data representation, statistical learning, linear regression, classification, resampling methods, tree-based methods, support vector machines, unsupervised learning, svd) • Artificial Intelligence & Machine Learning (Fundamental knowledge of probability, ML/DL models like Perceptron, MLP, SVM, CNN, RNN, GANs and al, Multi-Task/Cross-domain/Active and Incremental Learning, Unsupervised Learning, Reinforcement Learning.)

A curriculum designed to combine sport and study.