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Data Scientist - Job Opportunity at Mars

Haguenau, France

Full-time

Senior

Posted: July 25, 2025

On-site

€85,000 - €120,000 annually based on the senior-level requirements, 10+ years experience expectation, leadership responsibilities, and France's competitive data science market. The role's strategic importance to Mars' digital transformation and manufacturing optimization focus likely positions it in the upper end of this range, potentially reaching €130,000+ with bonuses.

Benefits

Industry competitive salary package with performance-based company bonus providing direct financial rewards tied to business success

Best-in-class learning and development support from day one including access to Mars University, offering continuous professional growth opportunities that exceed typical corporate training programs

Opportunity to work with diverse and talented associates guided by Mars' Five Principles, creating a values-driven collaborative environment

Purpose-driven mission involvement in building tomorrow's world today, providing meaningful work beyond traditional corporate objectives

Key Responsibilities

Lead strategic data science initiatives to optimize manufacturing processes across multiple global regions and plants, directly impacting operational efficiency and cost reduction

Drive digital transformation objectives for Pet Nutrition division through advanced analytics and machine learning implementations that reshape business operations

Manage complex multi-project portfolios simultaneously while delivering high-value insights that translate into measurable business outcomes

Develop and implement machine learning solutions, statistical analyses, and data visualizations that unlock hidden value from large-scale datasets

Create compelling data narratives and executive presentations that influence C-level decision-making and strategic business direction

Establish cross-functional collaboration frameworks with engineering, IT, and business stakeholders to ensure seamless project delivery

Build and mentor high-performing data science teams through coaching, code reviews, and knowledge transfer programs

Pioneer MLOps best practices including CI/CD pipelines, model lifecycle management, and production monitoring systems

Champion pet-centric analytical approaches that enhance product development and customer experience across all business divisions

Contribute to Mars' global data science community while advancing industry standards for consumer goods analytics

Requirements

Education

Degree or equivalent in Data Science, Mathematics, Statistics, or other numerate discipline. Nice to have – Master's / PhD with computing, scientific, statistical, or mathematical component.

Experience

10+ years' experience working as a Data Scientist. 5+ years varied technical experience in delivering statistical analytics, data science and insight on large-scale consumer data sets across multiple sectors, including packaged goods and retail. 3+ years of experience writing production-level code.

Required Skills

Great knowledge of Python and in particular, the classic Python Data Science stack (NumPy, pandas, PyTorch, scikit-learn, etc) Familiarity with PySpark A cloud platform experience (e.g Azure, AWS, GCP), we're using Azure in the team Good SQL understanding in practice Routine use and deep understanding of the best practices with version control, unit testing, CI/CD and in general, MLOps for model lifecycle management and monitoring Familiarity with containerization (Docker) and orchestration for scalable deployment Ability to write re-usable code Demonstrated ability to collaborate in a cross functional team including data engineer, data architect, general IT and non-technical stakeholders Demonstrable experience using data science and advanced analytics to generate business value and change, including optimisation of production processes Capacity and enthusiasm for coaching and mentoring less experienced data scientists, including code reviews, training sessions Must have excellent communication skills and interact effectively with all levels of internal business stakeholders in a global and multicultural environment

Sauge AI Market Intelligence

Industry Trends

The consumer packaged goods industry is undergoing massive digital transformation with companies investing heavily in IoT sensors, real-time manufacturing analytics, and predictive maintenance systems. Mars, being a global leader in pet care and confectionery, is positioning itself at the forefront of this Industry 4.0 revolution by embedding data scientists directly into manufacturing operations rather than keeping them in separate analytics teams. Manufacturing optimization through AI and machine learning has become a critical competitive advantage, with companies achieving 10-30% efficiency gains through predictive analytics, quality control automation, and supply chain optimization. The focus on pet nutrition specifically reflects the $240 billion global pet care market's rapid digitization and premiumization trends. There's a significant shift toward MLOps and production-ready data science, moving away from experimental notebook-based work toward enterprise-grade, scalable solutions. Companies are demanding data scientists who can not only build models but also deploy, monitor, and maintain them in production environments with proper CI/CD practices.

Role Significance

Based on the multi-disciplinary D&A team structure and mentoring requirements, this role likely involves leading or significantly influencing a team of 3-8 data professionals including junior data scientists, data engineers, and analysts, while collaborating across a broader network of 15-25 stakeholders in manufacturing, IT, and business units.

This is a senior individual contributor role with significant leadership influence, evidenced by the 10+ years requirement, mentoring responsibilities, stakeholder presentation duties, and strategic project ownership. The role sits at the intersection of technical expertise and business strategy, requiring someone who can drive organizational change through data science rather than simply execute predetermined analyses.

Key Projects

Manufacturing process optimization initiatives spanning multiple global facilities with potential cost savings in millions of euros through predictive maintenance, quality control automation, and production efficiency improvements Pet nutrition product development analytics leveraging consumer behavior data, nutritional science, and market trends to drive new product innovation and portfolio optimization Digital transformation infrastructure projects including cloud migration, data platform modernization, and MLOps pipeline establishment that will serve as the foundation for Mars' future analytics capabilities

Success Factors

The ability to translate complex technical concepts into compelling business narratives that drive executive decision-making and secure funding for data science initiatives, as this role requires regular stakeholder presentations and strategic influence across multiple organizational levels. Deep understanding of manufacturing operations and process optimization, going beyond generic data science skills to understand the nuances of production environments, quality control systems, and operational constraints that impact model deployment and business value creation. Strong leadership and team development capabilities, as the role explicitly requires mentoring and coaching responsibilities that will shape the next generation of Mars' data science talent while building organizational analytics maturity. Cross-cultural communication and collaboration skills essential for success in Mars' global, multicultural environment where projects span multiple regions and require coordination across diverse teams with varying technical backgrounds and business contexts.

Market Demand

Very High - Senior data scientists with manufacturing and consumer goods experience are in exceptional demand as traditional industries accelerate digital transformation initiatives, while the specific combination of MLOps expertise and business stakeholder management skills creates a supply shortage in the European market.

Important Skills

Critical Skills

Python and the data science stack (NumPy, pandas, PyTorch, scikit-learn) form the technical foundation for all model development and analysis work, with PyTorch specifically indicating the role involves deep learning applications for complex manufacturing optimization and consumer behavior modeling that require advanced neural network capabilities. MLOps and production code experience including CI/CD, version control, and model lifecycle management are essential because Mars operates at enterprise scale where model failures can cost millions in production losses, making reliable, maintainable systems critical for business continuity and stakeholder trust. Cross-functional collaboration and stakeholder communication skills are vital because data science value creation in manufacturing environments requires deep integration with engineering, operations, and business teams who have different technical backgrounds and success metrics, making translation between domains essential for project success.

Beneficial Skills

Azure cloud platform expertise aligns with Mars' technology stack and provides opportunities for advanced analytics capabilities, distributed computing, and integration with Mars' existing enterprise systems, while cloud skills generally position professionals for the industry's continued migration to cloud-native analytics platforms. Manufacturing domain knowledge and process optimization experience create significant competitive advantages in understanding operational constraints, quality requirements, and business impact measurement that generic data scientists often struggle with when transitioning into industrial applications. Mentoring and coaching capabilities become increasingly valuable as organizations build internal analytics capabilities and seek to develop talent rather than rely solely on external hiring, making leadership skills a key differentiator for senior data science professionals.

Unique Aspects

This role uniquely combines manufacturing optimization with consumer goods analytics, providing exposure to both operational efficiency challenges and consumer behavior insights that few other positions offer, creating a rare skill set combination highly valued in the Industry 4.0 landscape.

The pet-centric approach requirement represents Mars' commitment to purpose-driven analytics that goes beyond traditional business metrics to consider animal welfare and pet owner relationships, offering the opportunity to work on projects with genuine social impact alongside business value.

Direct involvement in Mars' global digital transformation strategy provides exceptional visibility into enterprise-scale change management and the opportunity to influence how a $45 billion company modernizes its operations across multiple continents and business units.

The combination of hands-on technical work with strategic business influence is unusual for data science roles, as most positions tend toward either pure technical execution or high-level strategy, while this role explicitly requires both deep technical skills and executive-level communication capabilities.

Career Growth

Typical progression to leadership roles within 2-4 years given the strategic nature of this position and Mars' investment in employee development through Mars University, with potential for faster advancement based on successful delivery of high-impact digital transformation projects and demonstration of business value creation.

Potential Next Roles

Head of Data Science or Chief Data Officer positions within Mars or similar multinational consumer goods companies, leveraging the strategic business exposure and team leadership experience gained in this role Senior Data Science Manager or Analytics Director roles in manufacturing-focused organizations, capitalizing on the specialized manufacturing optimization expertise and cross-functional project management skills Principal Data Scientist or Distinguished Engineer positions in cloud platforms or technology companies, building on the advanced MLOps, cloud architecture, and production system expertise developed through this role's technical requirements

Company Overview

Mars

Mars is a $45 billion privately-held global leader in pet care, confectionery, and food products, operating in over 80 countries with iconic brands like Pedigree, Whiskas, M&Ms, and Snickers. The company's private ownership structure allows for long-term strategic investments in innovation and digital transformation without quarterly earnings pressure, creating an environment where data science initiatives can focus on sustainable business impact rather than short-term metrics.

Mars holds dominant market positions across multiple categories, ranking as the world's largest pet care company and second-largest confectionery manufacturer. This market leadership provides access to massive, high-quality datasets across the entire value chain from raw materials to consumer behavior, creating unique opportunities for data science applications that smaller competitors cannot match.

The Haguenau location represents Mars' significant European manufacturing and innovation hub, housing both production facilities and R&D operations that serve the broader European market. This positioning provides exposure to Mars' complete European supply chain and manufacturing network, offering data science applications across multiple countries and regulatory environments.

Mars is renowned for its Five Principles (Quality, Responsibility, Mutuality, Efficiency, Freedom) which create a performance-driven yet collaborative culture that empowers employees to take ownership of their work and make impactful decisions. The company's focus on associate development through Mars University and internal mobility creates strong career advancement opportunities for high performers.

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Data Scientist - Job Opportunity at Mars

Benefits

Key Responsibilities

Requirements

Education

Experience

Required Skills

Sauge AI Market Intelligence

Industry Trends

Role Significance

Key Projects

Success Factors

Market Demand

Important Skills

Critical Skills

Beneficial Skills

Unique Aspects

Career Growth

Potential Next Roles

Company Overview

Mars

Data Sources & Analysis Information

Job Listings Data

Sauge AI Market Intelligence