Thomas Lecocq Email & Phone Number
@sillant.com
LinkedIn matched
Who is Thomas Lecocq? Overview
A concise factual answer block for searchers comparing this professional profile.
Thomas Lecocq is listed as Co-Founder and CTO (Chief Technology Officer) at Sillant, a with 3 employees, based in Greater Paris Metropolitan Region, France. AeroLeads shows a work email signal at sillant.com and a matched LinkedIn profile for Thomas Lecocq.
Thomas Lecocq previously worked as Deep Learning Engineer / Software Engineer at . and Senior Deep Learning Engineer at Adevinta. Thomas Lecocq holds Master Of Science (Ms), Data Science, Machine Learning, Data Analysis, Optimization Theory, Game Theory, Sociology from Ecole Nationale De La Statistique Et De L'Administration Économique.
Email format at Sillant
This section adds company-level context without repeating Thomas Lecocq's masked contact details.
AeroLeads found 1 current-domain work email signal for Thomas Lecocq. Compare company email patterns before reaching out.
About Thomas Lecocq
I am a Deep Learning Engineer with over eight years of experience in applying cutting-edge technologies and methodologies to create innovative solutions for various clients and industries. I have a Master of Science degree in Data Science from ENSAE, one of the leading French engineering schools, and a strong background in mathematics, statistics, and optimization.My current role involves engaging in advanced natural language processing (NLP) and computer vision (CV) tasks, leveraging state-of-the-art models and frameworks, such as LLaMA (1&2), Q-LoRA, Stable Diffusion, using Transformers and PEFT. I have also led the development of a unique software solution that harnesses collective intelligence and user preferences, introducing a novel way to interact with generative AI models. Additionally, I have designed and delivered in-depth NLP training programs for engineers, covering both theoretical and practical aspects of SotA models. I am proficient in Python, PyTorch, TensorFlow, Keras, Scikit-learn, AWS, Docker, Kubernetes, and other tools and platforms.
Listed skills include Machine Learning, Sentiment Analysis, Python, R, and 25 others.
Thomas Lecocq's current company
Company context helps verify the profile and gives searchers a useful next step.
Thomas Lecocq work experience
A career timeline built from the work history available for this profile.
Deep Learning Engineer / Software Engineer
CurrentLeveraging cutting-edge technologies and methodologies to create innovative solutions for clientsEngaged in advanced NLP tasks, primarily focusing on extending LLaMA and Llama 2 models through enhanced pre-training and fine-tuning. Leveraged state-of-the-art PEFT methods, including Q-LoRA, to improve instruction following via RLHF. Additionally, fine-tuned sentence-transformer models for specialized text classification purposes.I have led the development of a unique software solution utilizing the renowned AI image generation model Stable Diffusion. This initiative harnesses collective intelligence and user preferences, introducing a novel way to interact with the model. My role encompassed all aspects of the software's functionality, with a focus on Python for model operation, as well as the creation of a robust backend and database infrastructure for the application.I've used blockchain and smart contracts to tackle a range of challenges in the Web3 space, which included applying decentralized finance techniques to a new area. This effort contributed to the development of a unique solution. In this project, I worked closely with different teams to streamline processes, achieve our goals, and stay updated with the rapidly changing Web3 landscape.
Senior Deep Learning Engineer
Providing an API for content moderation for some of the biggest online marketplaces in the world, including Leboncoin (more than 5M messages moderated everyday)Designed and delivered in-depth NLP training programs for engineers, covering applications, theoretical foundations, and practical implementations of SotA models including GPT-3Environment :AWSDockerKubernetes (with Helm and Terraform)TravisSpinnakerJiraDataDog
Senior Data Scientist / Deep Learning Engineer
Creating and conducting Deep Learning training programs for colleagues and clients (180+ students & 20H+ of lectures)• Focused on both theoretical explanations and practical implementations of State-of-the-Art NLP models for English and French languages (special focus on CamemBERT, FlauBERT, GPT-2, ALBERT and ELECTRA)Carried out several Data Science projects for diverse clients• Segmented visitors and tailored recommendations of exhibitors for one of the biggest furniture trade show in Europe (Maison & Object by SAFI)• Implemented a novel customer segmentation methodology emphasizing on efficiency of means of communication for SoloInvest• Undertook initial analyses of the transaction databases of Century21 in cooperation with other colleaguesUse of : PyTorch, scikit-learn, SQL, GCP, AWS
Data Scientist / Deep Learning Engineer / Software Engineer
Designed and developed the AI engine for a startup specialized in customer journey analysisDec. 2019 - Jan. 2020• Adapted current state-of-the-art attention model for French language CamemBERT (nov. 2019) based on RoBERTa's architecture (jul. 2019, Facebook AI Research) in order to perform text classifications with very few training examplesDeveloped several automated cryptocurrencies-trading bots for a group of investorsOct. 2017 - Oct. 2019• Devised a prototype of a state-of-the-art algorithm for automated event-driven trading using CNNs applied to neural tensor networks’ event embeddings• Conceived, implemented and automated several innovative strategies to exploit the markets’ inefficiencies and trends• Arbitrated between 10+ marketplaces with very heterogeneous technicalitiesUse of : Pytorch, Tensorflow, Keras, transformers, Scrapy, Beautiful-Soup, Request, Flask
Data Scientist / Deep Learning Engineer
Worked on a software that analyzes data from any written medical source, to sum up patients’ cases and suggest medical diagnoses and potential alerts for health institutes• Used complex models including RNNs of GRUs/bi-LSTMs, own-trained word embeddings, transfer learning, multi-task learning, and zero-shot learning• Revamped and optimized our prototype’s data pipeline from the processing of the raw scans and models’ training to the actual predictions made inside our app• Read numerous research papers pertaining to diverse aspects of our models and domain of application to exploit the latest advances and most relevant techniques• Handled confidential data in a highly regulated field with no margin for error• Highly sparse, noisy and biased data and labels: 68K+ labels (ICD-10) with sometimes no incidence occurring for the last 10 yearsUse of : Tensorflow, Keras, Gensim, NLTK, Docker, GPGPU computing, Linux, SQL, Requests, Flasks
Data Scientist / Deep Learning Engineer
Project:• Built a generalist AI for Atari games combining reinforcement learning and deep learning using a technique pioneered by Goggle DeepMind in December 2013 called Deep Q-Learning => use of python's library Theano and RL-Glue to create the agent and interact with the Arcade Learning Environment => use of Lasagne on top of Theano and cuDNN for accelerated resultsA web site containing information about the procedures and results is available at https://deepqlearning.wordpress.com/• Solved a Kaggle competition with the use of Deep Learning => use of Keras and Lasagna libraries on top of Theano• Conducted a series of interviews with experts evolving in the Data Science industry and creation of a blog containing the published interviewshttp://datainterviews.com/Report:• Analysis of the Data-Science-as-a-Service ecosystem• Analysis of the evolution of the Deep Learning architectures• Analysis of the past evolution and prediction for the GPU market
Data Scientist / Machine Learning Engineer
Projects:• Developed sentiment analysis classifiers combining NLP methods with information extraction and machine learning algorithms in Python and R. => acquisition of insights regarding the emotional status, basic psychology and human values of the audience of one's Twitter accountsee "Explore your Twitter Audience Psychology" on http://labs.wisemetrics.com/• Developed a web tool to analyze users’ Twitter audience in order to rank them amongst other users and give insights about their followers. => development and smoothing of a ranking strategy and optimization of sampling and ranking methods to get an quick online grading of one's Twitter account• Developed internal tool to hunt for interesting hash-tags on Twitter and forecast the evolution of their future usage and impact on Twitter. => development of an hash-tags scoring strategy, sampling and forecasting of the score time-series• Designed and implemented innovative add-ins to the existing products.
Data Analyst
• Studied the penetration and market share of very high speed broadband regionally• Implemented statistical tools to report on evolution of key network performance indicators • Analyzed big databases (10M+ lines)
Thomas Lecocq education
Master Of Science (Ms), Data Science, Machine Learning, Data Analysis, Optimization Theory, Game Theory, Sociology
Classes Préparatoires Aux Grandes Ecoles – Mathematics And Physics Major
Frequently asked questions about Thomas Lecocq
Quick answers generated from the profile data available on this page.
What company does Thomas Lecocq work for?
Thomas Lecocq works for Sillant.
What is Thomas Lecocq's role at Sillant?
Thomas Lecocq is listed as Co-Founder and CTO (Chief Technology Officer) at Sillant.
What is Thomas Lecocq's email address?
AeroLeads has found 1 work email signal at @sillant.com for Thomas Lecocq at Sillant.
Where is Thomas Lecocq based?
Thomas Lecocq is based in Greater Paris Metropolitan Region, France while working with Sillant.
What companies has Thomas Lecocq worked for?
Thomas Lecocq has worked for Sillant, ., Adevinta, Ysance, and Collective Thinking.
How can I contact Thomas Lecocq?
You can use AeroLeads to view verified contact signals for Thomas Lecocq at Sillant, including work email, phone, and LinkedIn data when available.
What schools did Thomas Lecocq attend?
Thomas Lecocq holds Master Of Science (Ms), Data Science, Machine Learning, Data Analysis, Optimization Theory, Game Theory, Sociology from Ecole Nationale De La Statistique Et De L'Administration Économique.
What skills is Thomas Lecocq known for?
Thomas Lecocq is listed with skills including Machine Learning, Sentiment Analysis, Python, R, Sas, Linux, Deep Learning, and Reinforcement Learning.
Search by job title, company, industry, location, and seniority. Export verified B2B contact data when you need it.
Start free trialCheck these profiles if this is not the Thomas Lecocq you were looking for.
View similar profiles