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Lead Data Scientist
LATAM
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.
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