lavori da Intelligence Artificielle in località Francia

Job Description : 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 (e.g. PSO, GA, SGD).
• Experience with common development tools (e.g., PyCharm, Jupyter, Docker, Git).
• Excellent communication skills, both verbal and written.

Profile / Requirements :

BSc or MSc degree in a relevant field (e.g., Computer Science, Statistics). PhD degree is a plus.