{"id":2793440,"url":"https://alion.io/job/elsevier-manager-data-science-3","title":"Manager Data Science","company":{"id":3090,"name":"Elsevier","domain":"elsevier.com","url":"https://alion.io/company/elsevier","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":80,"open_postings":15,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":15,"computed_at":"2026-10-20T05:45:00Z"}},"role":"Science & Research","role_family":"Science & Research","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Amsterdam, Netherlands"],"countries":["NL"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":79000,"max":131500,"currency":"EUR","period":"year","gross":null,"usd_annual":147835},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"AI Agents","optional":false},{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"Haystack","optional":false},{"name":"Hugging Face","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false}],"status":"live","first_seen_at":"2026-09-02T00:00:00Z","employer_posted_date":"2026-09-02","last_verified_at":"2026-10-18T20:59:07Z","board_verified":true,"closed_at":null,"days_open":48,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":48},"description":"Manager Data Science - Corporate Markets, Life Sciences\nLocation: Amsterdam / London\nEmployment type: Full time\nAbout the team\nElsevier’s mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics.\nThe Corporate Markets Data Science team supports Elsevier’s Life Sciences products and platforms, including solutions used by pharmaceutical, biotechnology, chemistry, biomedical, and research organizations. Our work helps customers discover, connect, and act on high-quality scientific and clinical information across areas such as drug discovery, chemistry, biomedical research, clinical evidence, safety, and competitive intelligence.\nThe team applies a broad range of data science methods, including traditional machine learning, statistical modelling, natural language processing, neural networks, information retrieval, knowledge graphs, semantic enrichment, and generative AI. These capabilities support products such as PharmaPendium, Reaxys, Embase, and next-generation Life Sciences discovery platforms.\nAbout the role\nWe are looking for a Manager Data Science to lead a team of data scientists within the Corporate Markets Life Sciences area. You will set team direction, manage delivery, develop people, and ensure the team applies strong data science practices to solve complex business and customer problems.\nThis is a people-management role for a technically strong leader who can guide a team across a broad data science portfolio. The work may include machine learning models, NLP pipelines, entity extraction, classification, ranking, search, recommendation, data quality, knowledge graph enrichment, predictive analytics, LLM-based systems, Gen AI Agents, Multi Agent systems and RAG where relevant.\nYou will work closely with product, engineering, content, domain experts, and business stakeholders to deliver scalable, measurable, and production-ready data science solutions for Life Sciences customers.\nKey responsibilities\nLeadership & team management\nLead, coach, and develop a team of data scientists, supporting their technical growth, delivery, and career development.\nSet the strategy, priorities, and operating rhythm for the team in alignment with Corporate Markets and Life Sciences data science business goals.\nPlan, delegate, and manage team resources across multiple projects and product areas.\nCreate a culture of scientific rigor, collaboration, responsible AI, customer focus, and continuous improvement.\nGuide the team in defining and applying best practices for data science, experimentation, model evaluation, data quality, and production collaboration.\nData science delivery\nLead the application of data science methods across a broad portfolio, including machine learning, statistical modelling, NLP, neural networks, search, recommendation, knowledge graphs, and generative AI.\nOversee the development and improvement of models and pipelines for tasks such as classification, entity recognition, entity linking, document understanding, ranking, extraction, enrichment, prediction, and decision support.\nSupport the integration of structured and unstructured scientific data, including chemical entities, drugs, genes, diseases, clinical trials, safety data, publications, patents, metadata, and ontologies.\nGuide the use of modern AI approaches, including embeddings, LLMs, RAG, prompt-based workflows, and GenAI evaluation, where they add clear customer and business value.\nPartner with engineering to ensure solutions are robust, scalable, maintainable, and suitable for production use.\nEvaluation, experimentation & quality\nDefine and improve evaluation approaches for data science models, search systems, NLP pipelines, and AI-powered product features.\nEnsure appropriate use of metrics for model quality, retrieval quality, ranking performance, data accuracy, user outcomes, and business impact.\nGuide offline evaluation, A/B testing, error analysis, annotation workflows, and human-in-the-loop evaluation where needed.\nPromote responsible AI practices, including transparency, fairness, bias assessment, explainability, privacy, and risk management.\nEnsure the team makes evidence-based decisions and communicates results clearly to stakeholders.\nStakeholder collaboration\nWork closely with product managers, engineers, content specialists, ontology experts, biomedical informaticians, and commercial stakeholders.\nTranslate customer and business needs into clear data science opportunities, project plans, and measurable outcomes.\nCommunicate technical findings, trade-offs, risks, and recommendations to both technical and non-technical audiences.\nRepresent the team in cross-functional planning and contribute to the broader Life Sciences data science and AI strategy.\nRequired qualifications\nMaster’s, or PhD in Computer Science, Data Science, Machine Learning, Statistics, Bioinformatics, Cheminformatics, Information Retrieval, or a related field, or equivalent practical experience.\nAt least 5 years of experience in data science, machine learning, NLP, statistical modelling, information retrieval, or applied AI.\nExperience managing or leading technical teams directly.\nStrong understanding of data science methods, including supervised and unsupervised learning, Gen AI, statistical analysis, model evaluation, and experimentation.\nPractical experience with Python and common data science, machine learning, or NLP frameworks.\nExperience working with large, complex, structured and unstructured datasets.\nAbility to manage multiple projects, prioritize work, and deliver through others.\nStrong communication and stakeholder management skills.\nAbility to coach data scientists, review technical work, and improve team practices.\nExperience with LLMs, RAG pipelines, embeddings, GenAI evaluation, or human-in-the-loop annotation workflows.\nExperience with modern AI tools and platforms such as Databricks, PyTorch, Hugging Face, LangChain, LangGraph, Haystack, MLflow, or similar.\nPreferred qualifications\nExperience in life sciences, pharmaceuticals, chemistry, biomedical research, clinical data.\nFamiliarity with ontologies, taxonomies, controlled vocabularies, and metadata standards.\nExperience with NLP, entity extraction, entity linking, semantic enrichment, search, ranking, recommendation, or knowledge graph methods.\nExposure to production ML systems, MLOps, data pipelines, and model monitoring.\nWork in a way that works for you\nWe promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.\nFlexible working hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.\n\nAbout the business\nAs a global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.\n\nPrimary Location Base Pay Range: NLD Amsterdam (Radarweg) €79,000 - €131,500. \n\nThis role is covered by the Collective Labor Agreement Publishing Industry.\n\nWe know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Clickhereto access benefits specific to your location.\nWe are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.\nCriminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scamshere.\nPlease read our Candidate Privacy Policy.\nWe are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.\nUSA Job Seekers:\nEEO Know Your Rights.","description_format":"text","description_chars":8804,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Flexible schedule","Parental leave"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Publishing","Bioinformatics","Clinical Decision Support","Scientific & Lab Software"],"lifecycle":[{"event":"open","at":"2026-10-17T21:15:37Z"}],"visa":[],"liveness":{"score":11,"band":"cold","label":"Long shot","p_open":1,"p_active":0.404,"p_room":0.28,"age_days":48,"expected_fill_days":15,"reasons":["conf:32","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-20T05:45:00Z"},"pay":{"stated_usd_annual":147835,"is_top_pay":false},"html_url":"https://alion.io/job/elsevier-manager-data-science-3","json_url":"https://alion.io/job/elsevier-manager-data-science-3.json","meta":{"generated_at":"2026-10-20T09:48:53Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":10759,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-21T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":3090},"rest":"https://alion.io/mcp/rest/get_company?id=3090"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Felsevier-manager-data-science-3"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Felsevier-manager-data-science-3"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Felsevier-manager-data-science-3"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/elsevier-manager-data-science-3\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Felsevier-manager-data-science-3"}]}