Data Science Manager

• Lead, coach, and develop a team of data scientists
• Set team strategy, priorities, and operating rhythm aligned with Corporate Markets and Life Sciences goals
• Plan, delegate, and manage team resources across multiple projects and product areas
• Foster scientific rigor, collaboration, responsible AI, customer focus, and continuous improvement
• Define and apply best practices for data science, experimentation, model evaluation, data quality, and production collaboration
• Lead data science methods across machine learning, statistical modelling, NLP, neural networks, search, recommendation, knowledge graphs, and generative AI
• Oversee models and pipelines for classification, entity recognition, entity linking, document understanding, ranking, extraction, enrichment, prediction, and decision support
• Support integration of structured and unstructured scientific data
• Guide embeddings, LLMs, RAG, prompt-based workflows, and GenAI evaluation
• Partner with engineering on robust, scalable, maintainable, production-ready solutions
• Define evaluation approaches for models, search systems, NLP pipelines, and AI-powered product features
• Guide offline evaluation, A/B testing, error analysis, annotation workflows, and human-in-the-loop evaluation
• Promote responsible AI practices including transparency, fairness, bias assessment, explainability, privacy, and risk management
• Communicate evidence-based results, technical findings, trade-offs, risks, and recommendations
• Collaborate with product managers, engineers, content specialists, ontology experts, biomedical informaticians, and commercial stakeholders
• Translate customer and business needs into data science opportunities, project plans, and measurable outcomes
• Represent the team in cross-functional planning and contribute to Life Sciences data science and AI strategy

Requirements

• Master’s, or PhD in Computer Science, Data Science, Machine Learning, Statistics, Bioinformatics, Cheminformatics, Information Retrieval, or a related field, or equivalent practical experience
• Significant experience in data science, machine learning, NLP, statistical modelling, information retrieval, or applied AI
• Experience managing or leading technical teams directly
• Strong understanding of supervised and unsupervised learning, Gen AI, statistical analysis, model evaluation, and experimentation
• Practical experience with Python and common data science, machine learning, or NLP frameworks
• Experience working with large, complex, structured and unstructured datasets
• Ability to manage multiple projects, prioritize work, and deliver through others
• Strong communication and stakeholder management skills
• Ability to coach data scientists, review technical work, and improve team practices
• Experience with LLMs, RAG pipelines, embeddings, GenAI evaluation, or human-in-the-loop annotation workflows
• Experience with Databricks, PyTorch, Hugging Face, Lang Chain, Lang Graph, Haystack, MLflow, or similar
• Preferred: experience in life sciences, pharmaceuticals, chemistry, biomedical research, or clinical data
• Preferred: familiarity with ontologies, taxonomies, controlled vocabularies, and metadata standards
• Preferred: experience with NLP, entity extraction, entity linking, semantic enrichment, search, ranking, recommendation, or knowledge graph methods
• Preferred: exposure to production ML systems, MLOps, data pipelines, and model monitoring

Core Competencies

Demonstrates expertise in leading data science teams, applying machine learning and NLP techniques, and managing complex projects in alignment with corporate goals. Proficient in fostering collaboration, responsible AI practices, and translating business needs into actionable data science strategies.

Highest-signal resume keywords

• Data Science Leadership
• Machine Learning Expertise
• NLP Frameworks
• Project Management
• Responsible AI Practices

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Statistical Modelling
• Natural Language Processing
• Data Evaluation
• Supervised Learning
• Unsupervised Learning
• Data Quality
• Model Evaluation
• Experimentation
• Information Retrieval

Soft Skills

• Team Coaching
• Stakeholder Management
• Communication
• Collaboration
• Continuous Improvement

Certifications & Qualifications

• Master’s Degree
• PhD

Industry Keywords

• Life Sciences
• Pharmaceuticals
• Biomedical Research
• Clinical Data
• Ontologies
• Taxonomies
• Controlled Vocabularies
• Metadata Standards

Tools & Technologies

• Python
• Databricks
• Py Torch
• Hugging Face
• Lang Chain
• Lang Graph
• Haystack
• MLflow