{"id":3017415,"url":"https://alion.io/job/flexsis-data-scientist","title":"Data Scientist","company":{"id":2404928,"name":"Flexsis","domain":"flexsis.ch","url":"https://alion.io/company/flexsis","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":{"grade":"B","score":80,"open_postings":99,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":9,"computed_at":"2026-10-23T05:54:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Basel, Switzerland"],"countries":["CH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":94000,"max_usd":198000,"period":"year","method":"role_country_seniority_unknown","sample_n":14},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-10-21T09:28:49Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-10-23T17:30:42Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Flexsis is a company of the Interiman Group, one of the leading providers of personnel services in Switzerland. Thanks to our solid expertise as well as the competencies within the Interiman Group, we offer tailored solutions in personnel consulting.\nFor our client Novartis in Basel, we are looking for a reliable and motivated Data Scientist (m/f/d)\nDuration: 6 month - maternity cover\nWorkload: 80%\nKey Responsibilities:\nApplying established and novel approaches to model multi-modal clinical data to identify biomarkers predictive of disease progression and treatment response, and to nominate novel therapeutic target hypotheses\nDeveloping and applying a portfolio of pre-clinical models derived from internal and public data to departmental projects \nWorking closely with a core team of Translational Research & Data Science scientists fluent in wet and dry lab practices\nActively participating on interdisciplinary teams to model biology and guide impactful decision-making in drug discovery and early development \nActively participating in alliances with external partners at top healthcare institutions, including the opportunity to publish your findings\nEssential Requirements:\nLife sciences industry experience modeling biomedical research data\nDemonstrated working knowledge and application of statistics and data modeling to large scale life-sciences data • Hands-on experience in integration of large multi-omics data (genomics, transcriptomics, proteomics and metabolomics) to answer key scientific questions related to understanding disease\nHands-on industry experience with clinical data and its responsible handling\nHands-on experience applying AI and machine learning methods to scientific or R&D data\nExperience using AI tools, including large language models and agentic workflows, to accelerate analysis and decision-making \nProficiency in R/Python and competency working in a Linux environment\nReproducible research practitioner with demonstrated visualization and reporting skills\nA team-oriented, practical approach to problem solving\nMust haves:\nWorking knowledge and application of statistics and data modeling to large scale life-sciences data\nHands-on experience in integration of large multi-omics data (genomics, transcriptomics, proteomics and metabolomics) to answer key scientific questions related to understanding disease\nProficiency in R/Python and competency working in a Linux environment\nHands-on experience applying AI and machine learning methods to scientific or R&D data.\nExperience using AI tools, including large language models and agentic workflows, to accelerate analysis and 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