AI Data Scientist

Talan – Positive Innovation

Talan is an international consulting group specializing in innovation and business transformation through technology. With over 7,200 consultants in 21 countries and a turnover of €850M, we are committed to delivering impactful, future-ready solutions.

Talan at a Glance

Headquartered in Paris and operating globally, Talan combines technology, innovation, and empowerment to deliver measurable results for our clients. Over the past 22 years, we’ve built a strong presence in the IT and consulting landscape, and we’re on track to reach €1 billion in revenue this year.

Our Core Areas of Expertise

• Data & Technologies: We design and implement large-scale, end-to-end architecture and data solutions, including data integration, data science, visualization, Big Data, AI, and Generative AI.
  
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  Cloud & Application Services: We integrate leading platforms such as SAP, Salesforce, Oracle, Microsoft, AWS, and IBM Maximo, helping clients transition to the cloud and improve operational efficiency.
  
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  Management & Innovation Consulting: We lead business and digital transformation initiatives through project and change management best practices (PM, PMO, Agile, Scrum, Product Ownership), and support domains such as Supply Chain, Cybersecurity, and ESG/Low-Carbon strategies.
  

We work with major global clients across diverse sectors, including Transport & Logistics, Financial Services, Energy & Utilities, Retail, and Media & Telecommunications.

Job Description

• Data Analysis and Processing
  • Collect, clean, and prepare data from various sources (SQL databases, APIs, files, cloud).
  • Perform exploratory data analysis to identify patterns, trends, and anomalies.
  • Optimize data storage for cost and performance efficiency.
    
    

• AI/ML Solution Implementation and Monitoring
  • Build and train machine learning models to solve business problems (e.g., classification, regression, forecasting, NLP).
  • Monitor the performance of deployed models and update them when quality drops.
  • Create alert systems for data or model drift.
    
    
• Collaboration
  • Work closely with business teams to understand their needs and translate them into analytical/technical requirements.
  • Present analysis results and recommendations in a way that is clear for non-technical stakeholders.
    
    
• Visualization and Reporting
  • Build dashboards in BI tools (e.g., Power BI, Tableau, Qlik).
  • Create analytical reports and technical documentation.
    

Qualifications