EQUANS

Equans is a world leader in the energy and services sector, with annual revenues of nearly €19,2 billion* and almost 800,000 projects.​

Equans has leading positions in Europe, which is the result of the history of energy construction in these countries, and strong presences in North and South America and in Oceania.​

With nearly 90,000 highly skilled employees, Equans has a strong geographic footprint, anchored by historic local brands. Equans provides its customers with excellent technical expertise in the design, installation, maintenance and operation of multi-technical facilities. This know-how is based on key skills. First of all, in electrical and thermal engineering – two strong points that help accelerate the reduction of our clients’ carbon footprint – but also in ventilation, refrigeration, mechanics and robotics, fire protection, energy renovation, digital solutions, IT, cyber security and telecommunications.​

The combination of these expertise allows us to offer efficient and optimised solutions at all stages of the energy chain, from production, storage and transport to usage.

(*) Turnover 2024 consolidated

Lead Data Scientist (F/M)

Summary of the role

As Lead Data Scientist at Equans, you will combine hands-on technical expertise, community leadership, and team management to drive data science initiatives across the group. Your mission is to deliver high-quality, scalable data models while fostering collaboration, knowledge sharing, and skills development within a growing remote team. You will champion best practices, ensure governance compliance, and represent the data science community internally, accelerating the company’s digital and AI capabilities.

KEY METRICS OF THE ENVIRONMENT

– Datasources : More than 120 systems connected

– Interfaces : Distributing data to more than 30 production systems

– UseCases : 20 projects (5+ with AI embedded)

– Compute hours : 713K yearly compute hours

– Overall data community : ~10 countries

– Overall data community : ~80 Global Entreprise Items (Business Semantic Layer)

Key Objectives & KPIs

• Model deployment success rate: Percentage of prototypes successfully moved to production.
• Model performance and reliability: Metrics such as accuracy, latency, and uptime of deployed models.
• Community engagement level: Number of active participants and frequency of events in the data science community.
• Knowledge base coverage and update frequency: Volume and freshness of documented use cases and best practices.
• Reduction in duplicated efforts: Measurable decrease in redundant developments across teams.
• Team autonomy growth: Progress of the remote team towards operational independence.
• Compliance adherence: Percentage of data science projects meeting governance and traceability standards.
• Time to prototype: Average duration from concept to viable prototype.
• Stakeholder satisfaction: Feedback scores from internal business units and partners on data science deliverables.

KEY RESPONSIBILITIES

Technical Leadership

• Actively develop and maintain data pipelines, models, and testing frameworks.
• Rapidly prototype models with clearly defined stopping criteria.
• Select and advocate for the most relevant technical solutions (e.g., supervised models vs. LLMs) based on context.
• Ensure model quality, performance monitoring, cost control, and production readiness.
• Maintain shared coding standards, documentation, and code reviews.
• Conduct technological watch on LLMs, Retrieval Augmented Generation (RAG), AI agents, and ML innovations.
• Guarantee usage compliance with governance and traceability requirements.

Community Building

• Map data science activities, tool usage, project maturity across the organization.
• Animate and sustain a regular, autonomous, and friendly data science community.
• Manage a living knowledge base covering use cases, decisions, and lessons learned.
• Promote code and resource reuse to avoid repetitive bugs and redundancies.
• Organize skill development initiatives: workshops, pair programming, mentoring newcomers.
• Serve as data science ambassador to business units and partners.
• Evaluate project feasibility and say no when data science is not justified.
• Identify and nurture emerging data science talents.

Team Management

• Functional management of a remote and autonomous data science team based in India.
• Collaborate closely with the Head of Data for joint projects and alignment.
• Foster team skills growth and autonomy through coaching and empowerment.

PROFILE

Academic background & Experience

• Advanced Degree: Master’s or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Artificial Intelligence, or a closely related quantitative field.
• Solid Foundations: Strong knowledge in machine learning, statistical modeling, data engineering, and software development principles.
• Continuous Learning: Evidence of ongoing professional development through courses, certifications, or workshops in emerging AI technologies (LLM, RAG, MLOps, etc.).
• Community and Knowledge Management: Demonstrated ability to build and animate technical communities, foster collaboration, and disseminate best practices at scale.
• Full Pipeline Expertise: Comfortable working across the entire data science lifecycle—from data ingestion to model monitoring and maintenance, ideally within Palantir Foundry – 2/3 years experiences is required
• Cross-Functional Collaboration: Experience liaising between technical teams and business units, translating analytical insights into real-world impact and strategic value.
• Governance & Compliance: Familiarity with data governance, model compliance, and traceability standards in enterprise contexts.

Technical Skills

• Advanced expertise in applied data science, ML modeling, and production pipeline engineering.
• Strong proficiency in Python and data science frameworks.
• Experience with LLMs, RAG techniques, and AI model deployment.
• Ability to quickly prototype and iterate with clear technical criteria.
• Proven capability to establish and maintain coding standards, documentation, and reviews.
• Solid knowledge of data governance, compliance, and traceability practices.
• Excellent community-building and knowledge management skills.
• Fluent communication skills to act as an internal ambassador for data science.

Behavioral Capabilities​

• Leadership by example: maintain hands-on coding while managing and mentoring others.
• Collaborative mindset with strong community animation skills.
• Open, proactive in sharing knowledge and best practices.
• Decisive and able to say no when necessary to protect community focus.
• Adaptability to changing technical environments and priorities.
• Commitment to transparency, accountability, and continuous improvement.
• Cultural sensitivity to manage a multicultural remote team.
• Openness to innovation and emerging AI technologies.
• Resilience and positive attitude toward fast-paced, evolving challenges.

Why Join Us? 

• Global Reach: Influence EQUANS data strategy across continents and business units. Opportunity to work on projects at Bouygues Group level. 
• Technical Challenge: Work on PALANTIR data platform offering many uses. 
• Career Growth: Provision of IT teams from the Pluralsight platform* for the development of new skills.  
• Supportive Culture: Join a team that values innovation, transparency, and continuous learning. 

(*) Awarded the prize Best in Tech – Platinum Award 2025!