Data Scientist

Data ScientistBrand: Luxottica Wholesale North America Location: Dallas, TX, US, 75204 Position: Full-Time Total Rewards: Benefits/Incentive Information If you've worn a pair of glasses, we've already met. We are a global leader in the design, manufacture, and distribution of ophthalmic lenses, frames, and sunglasses. We offer our industry stakeholders in over 150 countries access to a global platform of high-quality vision care products such as the Essilor brand, with Varilux, Crizal, Eyezen, Stellest and Transitions, iconic brands that consumers love such as Ray-Ban, Oakley, Persol and Oliver Peoples, as well as a network that offers consumers high-quality vision care and best-in-class shopping experiences such as Sunglass Hut, LensCrafters, and Target Optical, and leading e-commerce platforms. Our portfolio of more than 150 renowned brands span various categories, from frames, lenses and instruments to brick and mortar and digital distribution as well as mid-range to premium segments. Our Shared Services Team, accompany and enable others within the EssilorLuxottica collective to achieve their targets. They keep people and projects running smoothly, ensuring every part of our business is provided for and well taken care of. Join our global community of over 200,000 dedicated employees around the world in driving the transformation of the eyewear and eyecare industry. This position is not available for visa sponsorship or transfer. Candidates must have authorization to work in the United States. Discover more by following us on LinkedIn!General Function: The Applied Data Scientist is a business-facing analytics professional responsible for AI research and solution delivery. The role owns the full problem-to-solution journey: engaging stakeholders, translating business challenges into ML solutions, researching emerging AI techniques, and delivering production-ready models that drive measurable business value. It balances innovation with execution, ensuring outcomes are practical, scalable, and aligned to business needs.Major Duties And ResponsibilitiesManaging: Engage with stakeholders to understand objectives, constraints, and success metricsDeliver end-to-end ML solutions from problem framing to production deploymentConduct applied research to evaluate and prototype new AI/ML techniquesPrioritize between research and delivery based on business impactManage model lifecycle: validation, monitoring, retraining, and optimizationOrganizingTranslate ambiguous business problems into structured data science statementsOrganize exploratory analysis, experimentation, and research frameworksStructure scalable ML pipelines for training, inference, and deploymentDevelop proof-of-concepts to validate new AI techniquesConvert insights and research outcomes into actionable recommendationsLeadingDrive solutions from research to productionAct as a trusted analytics advisor through consultative problem-solvingPromote adoption of ML solutions by communicating value and limitationsEvaluate and adopt emerging AI/ML techniquesMentor junior team members on research and delivery best practicesBasic QualificationsBachelor's degree in Computer Science, Data Science, Statistics, or related field5+ years of relevant work experienceProven experience delivering ML solutions in productionAbility to work independently with stakeholders and own deliveryStrong programming skills in Python or R; experience with ML libraries (scikit-learn, TensorFlow, PyTorch)Solid understanding of statistical modeling, ML techniques, and data miningPreferred QualificationsMaster's or PhD in Data Science, Statistics, or related disciplineExperience in applied research and rapid prototyping of AI/ML solutionsExposure to advanced AI techniques (deep learning, generative AI, optimization)Experience deploying ML models using Docker, Kubernetes, or cloud-native servicesFamiliarity with Azure, Databricks, Spark, Synapse, and Lakehouse architectureStrong storytelling and communication skills for technical and non-technical audiencesExperience in agile, fast-paced, cross-functional environmentsBalance research depth with delivery focusAbility to evaluate and apply new AI techniques pragmaticallyExcellent listening and problem-solving skillsStrong ownership mindset with minimal supervisionAbility to translate complex research into business value