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