{"id":3085745,"url":"https://alion.io/job/elsevier-manager-data-science-4","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":82,"open_postings":16,"ghost_share":0,"stale_share":0.938,"repost_share":0,"time_to_fill_p50_days":16,"computed_at":"2026-10-22T06:10:10Z"}},"role":"Data Science","role_family":"Data Science","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":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":102000,"max_usd":180000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":34},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"Hugging Face","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenSearch","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Qdrant","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Semantic Search","optional":false},{"name":"TensorFlow","optional":false},{"name":"AI Agents","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true}],"status":"live","first_seen_at":"2026-10-22T13:38:46Z","employer_posted_date":"2026-10-22","last_verified_at":"2026-10-22T18:05:42Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Interested in leading teams that build AI systems combining machine learning, retrieval, and modern language models to solve real-world problems?\nAbout the team:We’re looking for a Manager, Data Science to lead and develop a team of data scientists delivering intelligent, data-driven systems that help users explore, understand, and act on complex information.\nAbout the role: This is a people-management role for a technically strong leader. You will set direction for a portfolio of high-impact work, enable excellent execution through your team, and ensure robust, scalable, and trustworthy solutions move from concept to production. You will combine strong machine learning foundations with practical experience in modern AI approaches-including retrieval, ranking, and generation-to guide sound technical and product decisions.\nYou’ll work closely with engineering, product, and cross-functional partners to align priorities, develop talent, and raise the technical bar across the organisation.\nResponsibilities:\nLeadership & Team Management\nLead, coach, and develop a team of data scientists, supporting their technical growth, performance, and career development.\nSet team strategy, priorities, and operating rhythms aligned with product and business goals.\nPlan and manage team capacity across multiple initiatives, balancing short-term delivery with long-term technical investment.\nCreate an inclusive, high-performing culture grounded in scientific rigour, collaboration, customer focus, responsible AI, and continuous improvement.\nEstablish and evolve best practices for experimentation, model evaluation, data quality, production collaboration, and technical documentation.\nRecruit, retain, and develop strong data science talent.\nTechnical Direction & Delivery\nGuide the design and delivery of machine learning and AI-powered systems for complex, real-world problems.\nProvide technical leadership across a range of approaches, from classical machine learning to LLM-powered systems.\nOversee end-to-end solution delivery: problem framing, experimentation, evaluation, deployment, monitoring, and iteration.\nGuide the development of systems that combine retrieval, ranking, and generation to enable intelligent workflows.\nMake and support informed trade-offs between model performance, product needs, reliability, scalability, cost, and time to value.\nPartner with engineering to ensure solutions are robust, maintainable, secure, and suitable for production use.\nReview technical approaches and outputs, unblocking teams while maintaining appropriate hands-on technical depth.\nEvaluation, Impact & Responsible AI\nDefine evaluation strategies for machine learning models, retrieval systems, and AI-powered product features.\nEnsure teams use appropriate measures for model quality, retrieval and ranking performance, user outcomes, and business impact.\nGuide experimentation, error analysis, offline evaluation, online testing, and human-in-the-loop processes where appropriate.\nPromote responsible AI practices, including transparency, privacy, bias assessment, explainability, and risk management.\nEnsure technical decisions are evidence-based and that model behaviour, limitations, and risks are communicated clearly.\nCollaboration & Influence\nPartner with product, engineering, design, and other stakeholders to translate customer and business needs into clear data science opportunities and measurable outcomes.\nInfluence product and technical strategy through data-driven insights, recommendations, and pragmatic delivery plans.\nCommunicate technical findings, trade-offs, risks, and progress effectively to both technical and non-technical audiences.\nRepresent the data science team in cross-functional planning and contribute to the broader data and AI strategy.\nRequirements:\nCore Qualifications\nExstensive experience in data science, machine learning, or a related field.\nExperience directly managing, coaching, or leading data scientists or similarly technical professionals.\nStrong track record of delivering complex, production-quality data science or AI solutions through a team.\nDeep understanding of machine learning fundamentals, experimentation, statistical evaluation, and model performance assessment.\nStrong Python skills and the technical judgment to review and guide production-quality, maintainable systems.\nExperience working with large, complex, and unstructured datasets.\nAbility to manage multiple priorities, make sound trade-offs, and deliver.\nStrong stakeholder-management and communication skills.\nAI & Modern Techniques\nPractical experience with large language models in applied or production settings.\nExperience with retrieval-based approaches, including embeddings, semantic search, and ranking.\nExperience guiding or contributing to LLM-powered systems involving multi-step reasoning, tool use, or workflow orchestration.\nStrong judgment about when classical machine learning, retrieval, or LLM-based approaches are appropriate.\nExperience designing evaluation frameworks for AI-generated or retrieval-based outputs.\nData & Engineering\nFamiliarity with machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, and Hugging Face.\nExperience with cloud platforms and modern development workflows, including Git and CI/CD.\nUnderstanding of MLOps practices, including experiment tracking, deployment, monitoring, and reproducibility.\nExperience collaborating with engineering teams on scalable system design.\nFamiliarity with vector databases or search infrastructure such as Elasticsearch, OpenSearch, Qdrant, or similar.\nNice to Have\nExperience with search, information retrieval, recommendation, or knowledge systems at scale.\nExperience with agentic AI systems, workflow orchestration, or tools such as LangChain or LangGraph.\nExperience optimising AI systems for performance, scalability, reliability, or cost.\nExperience developing responsible AI governance or review practices.\nExperience building teams or leading organisational change in a data or AI environment.\nWhy Join Us\nLead a team working on impactful problems involving complex, real-world data.\nShape the technical and people strategy for systems combining machine learning fundamentals with modern AI approaches.\nPartner closely with product and engineering to deliver meaningful, scalable outcomes.\nDevelop talent while influencing the evolution of our data and AI capabilities.\nWork in a Way That Works for You\nWe promote a healthy work/life balance across the organisation. 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.\nWorking Pattern\nWorking flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive\nAbout the Business\nA 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 worl\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":8592,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Parental leave"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Publishing","Clinical Decision Support","Scientific & Lab Software"],"lifecycle":[{"event":"open","at":"2026-10-22T13:38:46Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":16,"reasons":["conf:3","win:early","comp:brand"],"computed_at":"2026-10-22T21:49:05Z"},"pay":null,"html_url":"https://alion.io/job/elsevier-manager-data-science-4","json_url":"https://alion.io/job/elsevier-manager-data-science-4.json","meta":{"generated_at":"2026-10-22T21:49:05Z","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":6571,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-23T00:00:00Z"}},"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-4"},{"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-4"},{"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-4"},{"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-4\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Felsevier-manager-data-science-4"}]}