Jérémie BLANCHARD

As a Senior Data Scientist at CRIM, I lead and develop applied AI projects in complex and high-constraint environments. My role spans the entire AI project lifecycle, from conception to industrialization, ensuring the delivery of robust, scalable, and explainable AI solutions. 💡 Key Responsibilities & Focus Areas: - End-to-end AI project management: from business need analysis to production deployment, addressing real-world constraints and uncertainties. - Model development & optimization: Applied AI, Machine Learning, Deep Learning, and MLOps. - Applied research & innovation: integrating cutting-edge AI advancements into practical use cases, balancing performance and feasibility. - Technology transfer & knowledge sharing: collaborating with businesses and institutions to ensure successful AI adoption and integration. 🚀 Impact & Achievements: - Managing high-impact AI projects worth over 300K CAD across multiple industries (healthcare, infrastructure, industrial applications). - Designing and deploying robust and explainable AI solutions that meet industry and regulatory requirements. - Supporting technical teams and experts to ensure successful AI solution adoption and integration.

As a Data Science and Business Intelligence Trainer at Le Wagon 4 Business, I have delivered 30+ training sessions and coached over 400 professionals in data analysis, AI, and business intelligence. My role involves designing and delivering high-impact training programs tailored to businesses and professionals looking to strengthen their data capabilities. 🎯 Key Responsibilities & Achievements: - Designed and led 30+ training sessions on Data Science, Machine Learning, and Business Intelligence, training over 400 professionals from various industries. - Facilitated a 5-day intensive training on Tableau & Business Intelligence: - Created a structured training program with hands-on exercises and interactive lessons. - Led sessions for cohorts of 20+ professionals. - Conducted follow-up meetings with clients to ensure alignment with business needs. - Supervised a Data Science Hackathon - Designed learning materials and real-world challenges. - Guided teams in solving complex data problems and presenting actionable insights.

As an independent Data Scientist, I supported businesses across various industries in strategic AI adoption and the development of data-driven solutions. My expertise covered the entire AI project lifecycle, from business need analysis to solution deployment. 🎯 Key Responsibilities & Contributions: - AI solution design & development: translating business needs into tailored technical solutions. Proof of Concept (PoC) & prototype development: machine learning, data analysis, and feasibility validation. - AI advisory & strategic guidance: educating teams on AI fundamentals and business impact. - End-to-end ML solution deployment: designing and implementing robust, scalable models. - Data visualization & reporting: creating dashboards to communicate insights effectively. - Project reinforcement & expert consulting: integrating into teams for specialized or temporary support. - AI training & knowledge sharing: delivering tailored training sessions for both technical and non-technical audiences.

I supported Ekwateur, an innovative energy provider, in integrating AI solutions to enhance customer service and optimize energy management. I worked on two strategic projects, from proof of concept (PoC) to full production deployment, enabling a better understanding of customer needs and improved energy purchasing strategies. 🎯 Key Projects & Achievements: - Customer sentiment analysis & NLP-based insights: - Developed and deployed a natural language processing (NLP) model to automatically analyze and categorize customer feedback. - Identified recurring issues and pain points to enhance customer service and streamline internal processes. - Electricity consumption forecasting - Designed and industrialized a demand forecasting model to optimize electricity purchasing. - Improved prediction accuracy, ensuring energy was bought at the right price and in the right quantity. - Training & AI adoption - Educated and trained technical and business teams on AI applications and methodologies. - Guided teams in leveraging AI models and integrating them into decision-making processes.

- Animation des formations chez JEDHA sur le thème du « Deep Learning », « Déploiement » et « Coaching Carrière ». - Animations des cours autour de sujets techniques - Correction des exercices avec les étudiants. - Accompagnement des élèves dans les exercices . - Accompagnement des élèves dans la réalisation d'un projet final de 10 jours.

As the CTO and co-founder of Unsaid, a startup specializing in emotion detection through Artificial Intelligence, I was fully responsible for the technical strategy and product development, from ideation to implementation. I led all technology-related aspects, aligning product vision, R&D, and market constraints to build an innovative NLP-based AI solution. 🎯 Key Responsibilities & Achievements: - Defined and executed the technology strategy: selected architectures, technologies, and methodologies to ensure product scalability and robustness. - Managed full product development: oversaw the entire development lifecycle, prioritizing technical needs based on market demands. - Led AI R&D efforts: designed and implemented cutting-edge NLP algorithms, combining statistical models and deep learning techniques. - Drove the technical roadmap: managed prototyping, validation, and industrialization phases for AI solutions. - Bridged R&D and business strategy: ensured a strong market-product fit by aligning research initiatives with commercial objectives. - Built and managed the technical team: recruited, trained, and guided engineers to deliver high-impact solutions. - Budget & funding management: optimized technical costs and secured funding to support the company’s growth.

Work in complete autonomy and realization of end-to-end Machine Learning solutions. Strong Natural Language Processing issues (Spacy, NLTK, Text Engineering and pre-processing) Development of Python scripts for the implementation of classification or prediction problems with the most recent algorithms. Examples of use cases treated : - Grouping of potentially linked support tickets - Forecasting the volume of tickets - Forecast of ticket processing time - Automatic ticket prioritization and scheduling Workshops with the product owner of the solution for the adjustment of the use cases and their functional integration to the solution. Workshops with the technical architect for the technical integration of the scripts in the solution and industrialization Presentations and workshops with customers Supervision of an intern Technical environment: Python, Elasticsearch, Azure Algorithms used : Prophet, K-Means, HCA, LSI, PCA, TruncateSVD, TF-IDF, fastcluster Participated in a project to predict failures and detect anomalies on a customer's critical applications. Realization of POCs around image recognition (Deep Learning, CNN)

Development of analytical POCs using Tableau Software and R. - Detection of fraud on ticket sales (e.g. abnormal refund rates) - Prediction of the percentage of refund - Analysis of the impact of particular events (e.g. strikes)

Writing of in-depth articles on various subjects: Video games, Multimedia, Cinema Writing news articles. Event coverage and production of reports and interviews.

International Master specialized in Machine Learning and Data Mining. Courses taught in English. Courses on Machine Learning, Data Mining, NLP, Big Data, Spark, Python, Deep Learning, Image Recognition.

Erasmus semester