NLP Data Scientist

Summary

Join Xebia, a global leader in digital solutions, and contribute your expertise to our team. You will work alongside data scientists and analysts to develop and deploy innovative product features across various platforms. This role demands expertise in machine learning, data engineering, and cloud technologies, particularly within the GCP ecosystem. You will be responsible for building scalable, efficient, and automated data processes, contributing to best practices, and working on cutting-edge Generative AI solutions. The ideal candidate possesses extensive experience in data engineering and machine learning deployment, along with strong programming skills and a deep understanding of cloud-based analytics. Xebia offers a collaborative environment focused on professional development and innovation.

Requirements

• 8+ years of experience as a data engineer or software developer
• 4+ years of experience developing and deploying machine learning systems into production
• Domain expertise relevant for retails banking, wholesale banking, tech, COO domains (e.g. financial crime and contact centers) and for building analytics platforms & data products
• Experience in prompt engineering, Agentic AI, RAG, information retrieval, LLM
• Expertise in evaluation, NLU, LLM inference tuning, LLM fine-tuning
• Knowledge of LLM, RAGs, prompt engineering, and productionizing LLM applications
• Familiarity with MLOps architecture and practices
• Strong programming skills like Python
• Expertise in public cloud (preferably GCP)
• Proficiency in managed GCP services (GKE, GCS, BQ, Dataproc, Dataflow), Cloud Storage, Cloud Run, Vertex AI suite (model garden, experiment, pipelines, etc.), BigQuery, and CI/CD steps and tooling such as Cloud Build and Artifact Registry
• Knowledge of public Cloud Analytics
• Relevant experience in sklearn, MLFLow, TensorFLow
• Very good verbal and written communication skills in English
• Work from the European Union region and a work permit are required

Responsibilities

• Work with data scientists and analysts to create and deploy new product features on the e-commerce website, in-store portals, and clients’ mobile apps
• Establish scalable, efficient, automated processes for data analysis, model development, validation, and implementation
• Write efficient and scalable software to ship products in an iterative, continual-release environment
• Contribute to and promote good software engineering practices across the team and building cloud-native software for ML pipelines
• Contribute to and reuse community best practices
• Work on Generative AI solutions to augment the CDD (Customer Due Diligence) review process
• Develop a risk summarization for at the end of a CDD Review

Preferred Qualifications

• Experience in Java, Scala, or Go
• Knowledge of AWS
• Experience in Kubernetes
• Expertise in Apache Airflow