Jobid=621616177141783433 (0.0199)
ph3Job description /h3pWe are looking for an AI/ML Data Scientist to accelerate RD across our health, nutrition, and beauty platforms by integrating and analysing multimodal biological and health data, enabling data-driven discovery and evidence generation for product innovation and claims. /ppThis role will contribute to building a reusable RD engine capable of systematically integrating internal and external multimodal datasets – spanning molecular/multi-omics, health, and lifestyle data – applying structured, reusable analytical frameworks and prioritising biologically plausible, health-relevant insights. Outputs from this work will directly inform discovery of healthy living and aging mechanisms, translate (pre)-clinical insights into product positioning hypotheses, and support claim substantiation. /ppThis role sits within SR Data Science AI – Quantitative Science team and works closely with cross-functional scientific and innovation teams to support all Business Units within dsm-firmenich. /ppstrongWhat You Will Do /strong /ppYou will contribute to building a digital RD framework capable of: /pulliSystematically ingesting large-scale external datasets and linking the generated insights to relevant internal assets to accelerate evidence generation. /liliIntegrating diverse data types including diet, lifestyle, host omics, microbiome data, and clinical outcomes to identify actionable biological patterns and high-confidence intervention targets. /liliIntegrating biological clocks, molecular signatures, and health-related endpoints to quantify intervention effects and identify mechanistic pathways. /liliPrioritising findings through AI/ML-assisted multi-criteria scoring frameworks that balance analytical robustness, biological plausibility, translational relevance, and novelty. /liliTranslating analytical results into structured scientific evidence packages that support product claims and commercial strategy. /li /ulpstrongKey Responsibilities /strong /pulliTranslate early-stage scientific and Business Unit questions into data-driven AI/ML-enabled analytical frameworks and projects that generate actionable targets and insights to guide strategic RD platform priorities. /liliDevelop scalable pipelines for external data ingestion, harmonisation, and multi-modal integration. /liliLeverage state-of-the-art AI tooling, including emerging agentic and generative AI approaches, to accelerate discovery, hypothesis generation, insight extraction, and interpretation of complex scientific results. /liliDesign and apply advanced AI/ML models to uncover non-linear relationships, generate hypotheses, and identify mechanistic links between interventions, host-microbiome biology, and health outcomes. /liliOperate effectively in ambiguous environments, prioritising analyses under uncertainty and balancing scientific depth with decision-making timelines. /liliCollaborate closely with Microbiome/Omics, Biostatistics, Trial Management, and Knowledge Management teams to build cross-functional analytical solutions and reusable assets. /liliLead and supervise internal and external contributors on analytical workstreams, ensuring methodological rigour, reproducibility, and alignment with project and business objectives. /liliContinuously monitor advances in AI/ML and their application to nutrition and clinical research and actively bring forward new ideas and methodological innovations to strengthen the RD portfolio. /liliCommunicate findings clearly to scientific, technical, and business stakeholders, contributing to evidence-based strategic decision-making. /li /ulpstrongWhat you bring /strong /ppstrongEducation Experience /strong /pulliPhD in a quantitative discipline such as Data Science, Machine Learning, AI, Computational Biology, Bioinformatics, Systems Biology or related field, with a strong commercial mindset and preferably 3+ years of industry experience; or /liliMSc with 5+ years of relevant industry experience in applied AI/ML within RD or health-related domains. /li /ulpstrongTechnical profile /strong /pulliDemonstrated experience working with large-scale multimodal biological and health datasets, including identifying, assessing, and ingesting relevant sources such as human cohort studies, omics datasets, and domain-specific scientific repositories. /liliStrong grounding in applied AI/ML for complex biological and health datasets, including longitudinal data structures, high-dimensional feature spaces, and robust model validation, with a demonstrated track record of applying these approaches in health, nutrition, biological, or clinical research contexts. /liliSolid expertise in integrative analysis of host and microbiome omics data, with focus on downstream modelling and insight generation rather than primary bioinformatics processing. /liliExperience integrating and harmonising cohort-based research datasets, including managing heterogeneous metadata structures and aligning variables across studies, is considered an advantage. /liliFamiliarity with agentic AI systems, generative AI, LLM-based pipelines, and AI-assisted knowledge synthesis is considered an advantage. /liliStrong coding skills in Python and/or R with emphasis on reproducibility, version control, modular pipeline development, and clear documentation. /li /ulpstrongWays of working /strong /pulliProactive, independent, self-starter who can translate open-ended scientific and commercial questions into structured, scalable analytical proposals. /liliComfortable operating at the interface of AI, biology, and product innovation. /liliStrong communicator capable of converting complex outputs into clear evidence narratives for scientific and business stakeholders. /liliSystems-oriented, with the ability to think beyond one-off analyses toward reusable evidence-generation infrastructure. /liliCurious, adaptable, and comfortable working in a fast-evolving, interdisciplinary environment. /liliExperience collaborating with cross-functional stakeholders across different regions and time zones is considered an advantage. /li /ulpstrongWe bring /strong /pulliA central role in shaping the organisation’s AI-driven target identification and prioritisation capabilities. /liliHigh degree of autonomy to define analytical approaches and propose new data-driven initiatives within a fast-evolving innovation landscape. /liliClose collaboration with innovation and commercial RD teams, enabling tangible societal and commercial impact. /liliAccess to cutting-edge internal and external datasets and leading (internal external) scientific expertise. /liliA translational environment where insights move from data to mechanisms to product hypotheses and claim strategies. /liliA collaborative, learning-focused environment across scientific and technical teams. /liliCareer development within a global, purpose-driven organisation. /li /ulh3About dsm-firmenich /h3pJoin our global team powered by science, creativity, and a shared purpose: to bring progress to life across health, nutrition, and beauty. /p /p #J-18808-Ljbffr
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