Data Scientist - Enterprise Search

Roche; Madrid; Híbrido; EUR 65.000 - 90.000; Jornada completa

Descripción de la vacante

Roche in Madrid is seeking a Data Scientist to lead Enterprise Search initiatives focused on Generative AI, LLMs, and vector-based data services. You will design AI-enabled search architectures, handle large datasets, and collaborate with cross-functional teams to improve accuracy and relevance.

Responsibilities include evaluating models, building scalable pipelines, and advancing MLOps. A hybrid work setup with office presence is expected, leveraging NLP, retrieval, and enterprise search

Formación

• Master’s degree or PhD in Data Science, CS, or related quantitative field.
• Proven track record delivering predictive models and analytical modules.
• Experience on moderately complex data problems within medium-scale architectures.
• Strong communication and collaboration with stakeholders.

Responsabilidades

• Lead model development, experimentation, and evaluation for AI-enabled solutions.
• Drive enterprise search innovation, exploring agentic patterns and RAG techniques.
• Develop embeddings, vector databases, and retrieval algorithms for scalable search.
• Partner with business stakeholders to translate problems into analytics and ML solutions.
• Contribute to PoC projects and knowledge-sharing sessions.

Conocimientos

Python

NLP

Information retrieval

Generative AI

Data analysis

Communication

Educación

Master’s degree in Data Science / CS

PhD is a plus

Herramientas

TensorFlow

PyTorch

scikit-learn

Elasticsearch

AWS / Azure

Descripción del empleo

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

The Position

Data Scientist - Enterprise Search role is responsible for contributing to the design and development of the next-generation Enterprise Search and information retrieval architectures. This role will build context-aware, generative AI-driven search systems optimized for agentic readiness—enabling autonomous tool orchestration, deep semantic understanding, and intelligent information retrieval at an enterprise scale. The data scientist will develop advanced AI solutions, with a strong focus on Generative AI, LLM-based applications, and scalable data services. This requires to work with large datasets, develop and evaluate machine learning models, and collaborate with cross-functional teams to improve the accuracy, coverage, relevance, and performance of search algorithms at enterprise scale. This role involves direct communication with project stakeholders and contributes to team best practices, while identifying optimization opportunities that enhance the impact of moderately complex data solutions within larger product architectures. You will leverage advanced technical skills to translate business needs into actionable data science initiatives.

Job Responsibilities

Generative AI, Agentic AI and LLM Optimization

• Model Development & Experimentation: Lead exploratory data analysis, feature engineering, model selection, training, validation, and performance evaluation for machine learning and AI-enabled solutions. Design and evaluate multiple modeling approaches, establish appropriate evaluation metrics, and optimize models for scalability, reliability, and business impact.
• Experimentation and Innovation: lead experimental projects and drive innovation in enterprise search, exploring novel approaches like GraphRAG or agentic search patterns.
• Agentic AI Search: Develop and deploy intelligent agentic architectures that can interact with and enhance the enterprise search experience
• RAG Experimentations (RAG Evaluation Framework): Design and conduct Retrieval-Augmented Generation experiments to evaluate and improve search relevance and performance
• LLM Model Evaluation: Evaluate the performance of Large Language Models in various enterprise search contexts, ensuring they meet business requirements and performance standards
• Advanced Prompt Engineering: Design and optimize prompts to programmatically enhance the interaction and effectiveness of search queries and responses

Business Problem Solving & Decision Support

• Partner closely with business stakeholders and product teams to translate complex business challenges into analytical approaches, ML solutions, and scalable intelligence capabilities.
• Support data-driven prioritization and strategic decision making through actionable insights, predictive models, and operational intelligence.
• Conducts A/B testing and experiments to assess the performance of search models and algorithms
• Consultancy Provide expert consultancy on data science and machine learning best practices, guiding internal teams and stakeholders
• PoC and knowledge sharing: Design and lead proof-of-value (PoV) projects, conduct knowledge-sharing sessions, and deliver impactful demos to showcase capabilities and gather feedback

Data Engineering & Vector Databases

• Data Engineering & Processing: Work with structured and unstructured data, building efficient pipelines for data ingestion, preprocessing, and feature engineering
• Vector database experimentation: Conduct experiments with vector databases to improve the efficiency and accuracy of our search systems
• Managing embeddings: Implement and optimize techniques for embeddings generation, indexation and retrieval to support advanced search queries and retrieval capabilities
• Retrieval & relevance tuning: Develop, evaluate, and tune retrieval algorithms to optimize search precision, recall, and relevance for diverse datasets
• Data quality: Design data enhancement modules that extract, enrich, and validate document content and metadata, directly improving downstream model context, search recall, and agentic reasoning

Model Lifecycle and integration

• Deployment, Testing, and Training of ML Models and Endpoints: Develop, deploy, and continuously refine machine learning models and endpoints to enhance search functionalities. Conduct rigorous testing and validation to ensure model accuracy and reliability
• Development of ML Models for search: Create and deploy advanced runnable models, such as entity extraction models and metadata augmentation, to expand the capabilities of our search solutions
• MLOps & Monitoring: Implement best practices for model deployment, versioning, monitoring, and performance optimization
• API & MCP Interoperability: Interface with enterprise search engines, platforms, and other APIs to enhance our search functionalities and integrations. Familiarity with MCP and protocols for agent interoperability

Qualifications

Education / Experience

• Master’s degree or PhD in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a related quantitative field.
• Demonstrated experience as a rising expert developing predictive models and leading specific analytical modules or project components
• Proven track record of taking full accountability for the quality and timely delivery of analytical tasks and troubleshooting complex data issues independently
• Experience working effectively on moderately complex data science problems and understanding how contributions fit into medium-sized data architectures

Technical Skills

• Shows strong proficiency in programming languages, particularly Python
• Has proven experience as a Data Scientist, preferably with a focus on information retrieval and NLP
• Has a solid understanding of natural language processing (NLP) techniques and tools
• Possesses hands-on experience with machine learning and deep learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn)
• Familiarity with cloud platforms and services, particularly AWS or Microsoft Azure
• Familiarity with version control systems (e.g., Git) and agile development practices
• Past experience with search engines and technologies (e.g. Elasticsearch, Solr, or Lucene) and solid understanding of search algorithms, information retrieval, and relevancy tuning is a plus
• Demonstrates excellent analytical and problem-solving skills, with the ability to work with large, complex datasets
• Proven ability to translate well-defined business questions into clear analytical problems and technical solutions

Additional Qualifications

• Strong communication and collaboration skills, with the ability to manage direct communication with immediate project stakeholders
• Ability to actively integrate feedback from technical peers and junior team members
• Proactive mindset to identify potential optimizations or new analytical approaches within the project scope
• Ability to work autonomously to achieve goals and deliver results, while actively collaborating with team members to meet shared team objectives.
• Experience in healthcare, pharmaceutical, or other regulated industries is a plus
• 40% monthly time working from the office is required ****

Who we are

A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.

Let’s build a healthier future, together.

Roche is an Equal Opportunity Employer.