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.
En 2011, Johan GUEDJ crée KLANIK avec la volonté de réinventer la place de l'ingénieur dans les sociétés de conseil, en le positionnant comme un acteur du rayonnement et du développement de son entreprise.
Le groupe KLANIK compte plus de 800 talents, évoluant dans 15 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 sur 5 pôles métiers :
• Software,
• DevOps & Cloud,
• Agilité,
• Cybersécurité,
• Data & IA.

Responsibilities

Job Description :

• 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.