Data scientist - tabular data h/f

KLANIK est une société de conseil en Ingénierie IT qui accompagne ses clients dans leurs projets digitaux et technologiques. Le groupe KLANIK compte désormais plus de 750 talents, évoluant dans 16 agences en Europe, Amérique du Nord, Afrique et Moyen-Orient. Des experts engagés, atypiques et passionnés, impliqués dans des projets stratégiques grâce à leur haut niveau de compétences en Software, DevOps, Cloud, Agilité, Cybersécurité, Big Data & IA. En parallèle de leurs métiers, les collaborateurs du groupe KLANIK sont accompagnés au quotidien dans leur développement personnel et professionnel, via différentes initiatives engageantes et innovantes : KONSCIOUS : communauté interne engagée dans les enjeux écologiques, sociaux et environnementaux KAMPUS : institut de formation technique certifié KORNER : incubateur de start-ups technologiques KLANIK ESPORT : club professionnel e-sport ouvert aux collaborateurs Le poste : Responsibilities • Understanding business objectives and developing AI solutions that help to achieve them, along with metrics to track their progress. • Prepare, clean, and preprocess data for analysis. • Analyze data quality and proactively address issues. • Develop data-driven algorithms for clustering, classification, regression, and optimization. • Evaluate AI solutions aligned with business objectives. • Deploy and manage AI models in production. • Identify differences in data distribution that could potentially affect model performance in real-world applications. • Analyzing the errors of AI models and designing strategies to overcome them. • Maintain and enhance existing solutions to meet evolving business needs. • Visualize and communicate results analysis effectively. • Present ideas, plans, and findings orally and in written reports. • Collaborate with data scientists, data engineers, and software engineers on production applications. Experience • 5 years of experience demonstrating depth and breadth in state-of-the-art machine-learning, deep learning and optimization. • Demonstrated experience in developing core AI algorithms in industry or for real-world problems. • Proven track record of implementing robust and scalable industrial AI solutions. • Strong understanding of the unique challenges and complexities involved in optimization. • Experience in implementation of MLOps pipelines is a plus. • Experience in the Oil & Gas industry is a plus. Key Skills • Strong background in applied mathematics, algorithms, and coding. • Proficiency in statistics, machine learning, and deep learning. • Proficiency in Python programming and data analysis libraries (e.g., Pandas, NumPy). • Proficiency in data manipulation, cleaning, preprocessing and feature engineering - • Proficiency in deep learning frameworks (e.g. Keras, PyTorch). • Theoretical and practical knowledge of popular machine learning algorithms (e.g., PCA, Support Vector Machines, RandomForest, XGBoost, skforecast). • Theoretical and practical knowledge of popular optimization methodologies (ex. PSO, GA, SGD'). • Experience with common development tools (e.g., PyCharm, Jupyter, Docker, Git). • Excellent communication skills, both verbal and written. Profil recherché : BSc or MSc degree in a relevant field (e.g., Computer Science, Statistics). PhD degree is a plus. Key Skills • Strong background in applied mathematics, algorithms, and coding. • Proficiency in statistics, machine learning, and deep learning. • Proficiency in Python programming and data analysis libraries (e.g., Pandas, NumPy). • Proficiency in data manipulation, cleaning, preprocessing and feature engineering - • Proficiency in deep learning frameworks (e.g. Keras, PyTorch). • Theoretical and practical knowledge of popular machine learning algorithms (e.g., PCA, Support Vector Machines, RandomForest, XGBoost, skforecast). • Theoretical and practical knowledge of popular optimization methodologies (ex. PSO, GA, SGD'). • Experience with common development tools (e.g., PyCharm, Jupyter, Docker, Git). • Excellent communication skills, both verbal and written. Source : PMEjob.fr.