Data Scientist

Permanent contract

27 Jan 2026

    Akkodis is looking for a skilled Data Scientist to support high-impact data-driven projects for one of its prominent clients, notably in industrial sectors.

    The Data Scientist is responsible for designing, developing, and deploying advanced analytics and machine learning solutions that generate actionable insights across business units at a pan-European level.

    The role involves close collaboration with business stakeholders, data engineers, and product teams to translate complex data into scalable analytical solutions.

    Role

    Analyze, clean, and preprocess large and complex datasets using Python and SQL
    Explore data to identify patterns, trends, and opportunities for advanced analytics
    Design, develop, and deploy machine learning models including predictive models, recommendation systems, anomaly detection, and optimization algorithms
    Apply statistical methods to validate models and interpret results
    Perform time series analysis and forecasting for operational and business use cases
    Collaborate with data engineers to ensure efficient data pipelines and model deployment
    Use platforms such as Dataiku DSS to develop, train, deploy, and monitor models
    Visualize data and model outputs to communicate insights clearly to stakeholders
    Translate analytical findings into actionable business recommendations
    Document models, assumptions, and methodologies to ensure transparency and reproducibility
    Contribute to best practices, standards, and continuous improvement in data scienc

    Your profile :

    Master’s degree in Science, Engineering, Mathematics, Statistics, or related field
    Minimum 3 years of professional experience as a Data Scientist
    Experience in industrial environments is a strong plus
    Strong proficiency in English (written and spoken)
    Ability to work in a multi-cultural and international environment
    Data Science and advanced analytics
    Strong programming skills in Python (pandas, NumPy, scikit-learn, etc.)
    Solid SQL knowledge for data exploration and analysis
    Machine Learning techniques: supervised and unsupervised learning, recommendation systems, anomaly detection
    Statistical analysis and validation methods
    Time series forecasting and optimization techniques
    Experience with Dataiku DSS (certification required)
    Familiarity with cloud data platforms such as Snowflake
    Data visualization tools (e.g. Python libraries, BI tools)
    Understanding of model deployment and monitoring concepts