Lead Data Scientist

For more than 20 years, our global network of passionate technologists and pioneering craftspeople has delivered cutting-edge technology and game-changing consulting to companies on the brink of AI-driven digital transformation. Since 2001, we have grown into a full-service digital consulting company with 5500+ professionals working on a worldwide ambition.

Driven by the desire to make a difference, we keep innovating. Fueling the growth of our company with our knowledge worker culture. When teaming up with Xebia, expect in-depth expertise based on an authentic, value-led, and high-quality way of working that inspires all we do.

About the Role

As a Lead Data Scientist, you will operationalize innovative AI/ML solutions and work alongside other team members like Product Manager, Enterprise Architect, ML Engineers[SP2] [NB3] , Data scientists and Business to architect, design, build and productionalize AI/ML models. You will be also responsible for integrating AI/ML solutions into operational products. This hands-on technical role demands excellent Data Science, ML engineering and ML ops/LLM Ops knowledge and can demonstrate best practices in the industry. Come be a part of a team that is starting this new journey.

We are looking for someone who is a technology-agnostic polymath—committed to a lifelong journey of learning and exploration of new scientific ideas—and will bring thoughtful perspectives, empathy, creativity, and a positive attitude to solve problems at scale. This role is ideal for someone looking to extend their Data Science, machine learning and software engineering skills to lead an AI/ML engineering team and create impact by delivering AI/ML capabilities at scale

What You’ll Do

• Responsible for leading and executing AI/ML solutions across enterprise

• Architect, build, maintain scalable systems using established design patterns, leads security-first practices, and maintains deep domain expertise while anticipating future technical needs and costs

• Implement end-to-end solutions for batch and real-time algorithms along with tooling around monitoring, logging, automated testing, performance testing and A/B testing

• Collaborate with Product, Engineering, Data Scientists, ML Engineers and Business teams on planning new capabilities

• Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation

• Write efficient and well-organized software to ship products in an iterative, continual-release environment

• Actively participate in code review to ensure it meets best practice specifications and drive quality assurance through systematic testing frameworks and debugging

• Contribute to and promote good software engineering practices across the team

• Reviews and prioritizes epics/projects with proper breakdown and dependency management, proactively identifies and communicates blockers or delays, handles uncertainty and high-pressure situations decisively, and applies economic thinking to optimize value delivery

• Mentor teammates to adopt best practices in writing and maintaining production machine learning code and growth opportunities, fosters cultures of effective communication, feedback, and knowledge sharing, builds strong cross-functional relationships, and collaborates on engineering strategy while contributing to product roadmap development.

• Excellent communication skills, with the ability to explain complex technical concepts to technical and non-technical audiences

• Utilize your entrepreneurial spirit to identify new opportunities to optimize business processes and improve consumer experiences, and prototype solutions to demonstrate value with a crawl, walk, run mindset.

• Demonstrate our values of Passion for Client Service, Innovation, Expertise, Balance, Respect for All, Teamwork, and Initiative

• Support technical evaluations of other consultants when required, contributing to the assessment of skills and alignment with project needs

What You Bring

• University or advanced degree in engineering, computer science, mathematics, or a related field

• 5+ years of experience developing and deploying machine learning systems into production

• 8+ years of experience in Software Engineering

• Experience working with AI Agentic systems, LLMs, and RAG architecture

• Experience working with MCP (Model Context Protocol)

• Experience using open source LLMs and LLMOPs

• Experience working with a variety of relational SQL and NoSQL databases

• Experience working with: Spark, Kafka, Scala, Python, etc.

• Knowledge of cloud platforms (Azure, AWS or equivalent cloud platforms)

• Microsoft Azure: Experience designing, deploying, and administering scalable, available, and fault tolerant systems on Microsoft Azure

• Hands-on Experience working with Databricks

• Hands-on Experience working with Claude

• Experience with deep learning frameworks such as PyTorch, TensorFlow, Keras or similar

• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

• Industry experiences building and productionizing creative end-to-end Machine Learning systems

• Experience building and operationalizing feature stores

• Experience working with distributed systems, service-oriented architectures, and designing APIs

• Familiarity in deploying real-time ML systems on Azure Cloud through frameworks such as ONNX, MLEAP, TF Serving, etc.

• Knowledge of data pipeline and workflow management tools

• Expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation

• Relevant working experience with Kubernetes.

What We Offer

• 100% remote work to provide flexibility and work-life balance.

• Company laptop and necessary equipment to perform your role effectively.

• Competitive salary package aligned with local market benchmarks.

Xebia is committed to creating an inclusive and diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability or age.