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Lead Data Scientist
AtkinsRéalisLead Data Scientist heading AI/ML initiatives, designing ML models and mentoring data scientists at AtkinsRéalis. Collaborating with engineering and business teams to deliver scalable, production-grade models.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in defining and executing AI/ML strategies, with a strong focus on deploying advanced ML/DL models and MLOps pipelines. Proven ability to mentor teams and engage stakeholders to translate business challenges into AI solutions.
Highest-signal resume keywords
AI/ML Strategy ExecutionDeep Learning Libraries (PyTorch, TensorFlow, Hugging Face)Azure Cloud Experience (Azure ML, Azure Blob, Azure OpenAI)MLOps Pipeline DevelopmentComputer Vision and Generative AI
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonMachine LearningDeep LearningComputer VisionGenerative AINatural Language UnderstandingMLOpsVersion ControlCI/CDAgentic AI Principles
Soft Skills
Strong CommunicationProblem SolvingMentoring
Tools & Technologies
Azure AI StackCognitive ServicesOpenAILangChainSemantic Kernel
Industry Keywords
AI ProjectsModel ExplainabilityFairness in AIAutonomous OrchestrationData Science Leadership
Tech Stack
Tools & technologiesAzureCloudPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Define and lead the execution of AI/ML strategies aligned with organizational goals.
- Design and deploy advanced ML/DL models including LLMs, GANs, and CV solutions.
- Implement agentic AI systems that support autonomous orchestration of complex tasks.
- Development of MLOps pipelines for versioning, retraining, testing, and deployment.
- Champion best practices for experimentation, model explainability, and fairness.
- Collaborate with cloud engineering teams to ensure seamless integration on Azure AI stack (e.g., Azure ML, Cognitive Services, OpenAI).
- Mentor and review the work of junior and mid-level data scientists, ensuring quality and innovation.
- Engage with business stakeholders to translate challenges into AI opportunities.
Requirements
What you’ll need- 10+ years of experience in data science, ML, or AI, with at least 3 years in a team/tech leadership role.
- Proficiency in Python and deep learning libraries such as PyTorch, TensorFlow, Hugging Face, OpenCV.
- Extensive experience in computer vision, generative AI, and natural language understanding.
- Deep knowledge of agentic AI principles and orchestration tools (LangChain, Semantic Kernel, etc.).
- Proven Azure cloud experience: deploying models via Azure ML, handling data via Azure Blob/Data Lake, using Azure OpenAI services.
- Strong grasp of software engineering practices – version control, testing, CI/CD for ML (MLOps).
- Strong communication and problem solving skills.
- Ability to articulate complex technical concepts to non-technical audiences.
- Proven track record in delivering AI projects to production and scaling them.
Benefits
Comp & perks- Comprehensive life insurance coverage.
- Premium medical insurance for you and your dependents.
- Generous annual leave balance.
- Flexible and hybrid work solutions.
- Remote work opportunities outside of country.
- Company gratuity scheme.
- Discretionary bonus program.
- Relocation assistance.
- Employee Wellbeing Program: 24/7 access to specialists in finance, legal matters, family care, personal health, fitness, and nutrition.