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Data Scientist - Foundation Models for Time Series Prediction - Job Opportunity at DatumLocus

Lille, France
Contract
Mid-level
Posted: April 16, 2025
On-site
EUR 45,000 - 65,000 per year, based on Lille market rates for specialized ML roles

Benefits

Continuous learning and development opportunities
Potential permanent contract conversion
Modern tech ecosystem within Euratechnologies
Flexible work environment
Professional development through cutting-edge projects

Key Responsibilities

Lead research and implementation of state-of-the-art foundation models (TimeGPT, Chronos, TimesFM)
Design and optimize time series embedding and vectorization systems
Develop innovative hybrid architectures combining transformers with traditional neural networks
Conduct comprehensive model testing and validation across multiple datasets
Drive implementation of production-ready forecasting solutions

Requirements

Education

Master's/PhD in Data Science, Econometrics, or Applied Statistics, or Engineering degree

Experience

Previous professional experience as Data Scientist required

Required Skills

Programming proficiency in R, Python, or Rust Time series forecasting expertise Foundation models and transformer architectures Professional English proficiency Cloud services (AWS/Azure) preferred MLOps tools (HuggingFace, Docker, Kubernetes) Econometrics knowledge
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Sauge AI Market Intelligence

Industry Trends

The agrifood sector is experiencing rapid digital transformation, with AI-driven forecasting becoming crucial for supply chain optimization and waste reduction Foundation models are revolutionizing time series prediction, showing superior performance compared to traditional statistical methods The convergence of ML and domain-specific knowledge in food industry analytics is creating unique opportunities for specialized data scientists

Role Significance

Likely part of a small but growing technical team (3-7 people) typical of an innovative startup in the ML space
Mid-level technical position with significant research and development responsibilities, indicating a balance between implementation and innovation

Key Projects

Development of custom foundation models for food industry time series Integration of hybrid ML architectures for improved forecasting accuracy Implementation of scalable MLOps systems for model deployment

Success Factors

Deep understanding of both classical time series methods and modern deep learning approaches Ability to bridge theoretical ML concepts with practical business applications Strong research orientation combined with implementation capabilities Collaborative mindset for working in a startup environment

Market Demand

High demand with growing trajectory due to increasing adoption of AI in supply chain management and specific expertise in foundation models

Important Skills

Critical Skills

Deep understanding of transformer architectures and foundation models is essential for core role responsibilities Time series analysis expertise bridges classical methods with modern ML approaches Strong programming skills needed for complex model implementation

Beneficial Skills

Cloud infrastructure knowledge enables scalable solution deployment MLOps expertise supports production-ready system development Econometrics background helps in understanding underlying business metrics

Unique Aspects

Focus on foundation models for time series specifically in food industry applications
Hybrid architecture development combining multiple ML paradigms
Direct application of cutting-edge ML research to practical industry challenges

Career Growth

2-3 years potential for advancement given startup growth trajectory and specialized expertise development

Potential Next Roles

Lead Data Scientist ML Engineering Manager AI Research Scientist Technical Product Manager

Company Overview

DatumLocus

Early-stage startup focused on innovative ML applications in the agrifood sector, positioned at the intersection of AI research and practical business solutions

Emerging player in the specialized ML solutions market, with potential for significant growth in the agrifood tech sector
Strategic location in Euratechnologies, Lille's premier tech hub, providing access to resources and talent
Innovation-driven startup environment with emphasis on technical excellence and practical impact
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