Data Scientist
EssilorLuxottica · Dallas, TX · 1 wk ago
EngineeringFull-time
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 Responsibilities
- Engage with stakeholders to understand objectives, constraints, and success metrics
- Deliver end-to-end ML solutions from problem framing to production deployment
- Conduct applied research to evaluate and prototype new AI/ML techniques
- Prioritize between research and delivery based on business impact
- Manage model lifecycle: validation, monitoring, retraining, and optimization
- Translate ambiguous business problems into structured data science statements
- Organize exploratory analysis, experimentation, and research frameworks
- Structure scalable ML pipelines for training, inference, and deployment
- Develop proof-of-concepts to validate new AI techniques
- Convert insights and research outcomes into actionable recommendations
- Drive solutions from research to production
- Act as a trusted analytics advisor through consultative problem-solving
- Promote adoption of ML solutions by communicating value and limitations
- Evaluate and adopt emerging AI/ML techniques
- Mentor junior team members on research and delivery best practices
Basic Qualifications
- Bachelor’s degree in Computer Science, Data Science, Statistics, or related field
- Proven experience delivering ML solutions in production
- Ability to work independently with stakeholders and own delivery
- Strong programming skills in Python or R; experience with ML libraries (scikit-learn, TensorFlow, PyTorch)
- Solid understanding of statistical modeling, ML techniques, and data mining
PREFERRED QUALIFICATIONS
- Master’s or PhD in Data Science, Statistics, or related discipline
- Experience in applied research and rapid prototyping of AI/ML solutions
- Exposure to advanced AI techniques (deep learning, generative AI, optimization)
- Experience deploying ML models using Docker, Kubernetes, or cloud-native services
- Familiarity with Azure, Databricks, Spark, Synapse, and Lakehouse architecture
- Strong storytelling and communication skills for technical and non-technical audiences
- Experience in agile, fast-paced, cross-functional environments
- Balance research depth with delivery focus
- Ability to evaluate and apply new AI techniques pragmatically
- Excellent listening and problem-solving skills
- Strong ownership mindset with minimal supervision
- Ability to translate complex research into business value
Basic Qualifications
- Bachelor’s degree in Computer Science, Data Science, Statistics, or related field
- Proven experience delivering ML solutions in production
- Ability to work independently with stakeholders and own delivery
- Strong programming skills in Python or R; experience with ML libraries (scikit-learn, TensorFlow, PyTorch)
- Solid understanding of statistical modeling, ML techniques, and data mining
PREFERRED QUALIFICATIONS
- Master’s or PhD in Data Science, Statistics, or related discipline
- Experience in applied research and rapid prototyping of AI/ML solutions
- Exposure to advanced AI techniques (deep learning, generative AI, optimization)
- Experience deploying ML models using Docker, Kubernetes, or cloud-native services
- Familiarity with Azure, Databricks, Spark, Synapse, and Lakehouse architecture
- Strong storytelling and communication skills for technical and non-technical audiences
- Experience in agile, fast-paced, cross-functional environments
- Balance research depth with delivery focus
- Ability to evaluate and apply new AI techniques pragmatically
- Excellent listening and problem-solving skills
- Strong ownership mindset with minimal supervision
- Ability to translate complex research into business value
Total Rewards
- Benefits/Incentive Information