Senior Data Scientist - Artificial Intelligence R&D
Role details
Job location
Tech stack
Job description
Join the AI Research & Development team of Cat Digital and play a central role in advancing the frontier of applied AI for one of the world's largest industrial enterprises. As a Senior Data Scientist, you will design, build, and evaluate cutting-edge AI systems, spanning generative AI, large language models (LLMs), multimodal intelligence, retrieval-augmented generation (RAG), and autonomous agents, delivering high-impact Proofs of Concept (POCs) with clear production intent while exploring longer-horizon research opportunities., * Design and execute AI experiments across the full model lifecycle: hypothesis formulation, data preparation, model development, evaluation, and iteration, maintaining research rigor in an ambiguous, fast-moving environment.
- Develop, fine-tune, and benchmark LLMs and multimodal AI models (text, vision, speech), including systematic evaluation of quality, latency, cost, and safety tradeoffs across model variants and providers.
- Explore and optimize knowledge retrieval systems (RAG pipelines, vector databases, hybrid search) and agentic workflows, ensuring relevance, accuracy, and scalability for enterprise use cases.
- Lead data preparation workstreams for model training, fine-tuning, and validation, including dataset curation, labeling strategy, synthetic data generation, and quality assurance.
- Instrument AI systems for observability and reproducibility using experiment tracking frameworks (e.g., Langfuse, MLflow), maintaining clear documentation of model versions, evaluation datasets, and performance baselines.
- Translate research findings into production-ready prototypes, collaborating with Engineering and Product teams to define technical requirements, integration paths, and deployment readiness criteria.
- Evaluate emerging AI capabilities and tools (open-source and commercial), providing structured assessments and recommendations to inform the team's technology strategy.
- Mentor and coach junior Data Scientists, establishing best practices for experimentation, model evaluation, and responsible AI development across the team.
- Communicate insights and results to technical and non-technical stakeholders, including product managers, engineers, and senior leadership, with clarity and business impact framing.
Requirements
- Applied Statistics & Quantitative Methods: Experience applying statistical thinking to experimentation, evaluation, and decision-making in ambiguous, research-driven environments.
- Analytical Rigor & Attention to Detail: Proven ability to design precise experiments, validate assumptions, and ensure accuracy and reproducibility of results.
- Advanced Machine Learning & AI: Knowledge of modern ML techniques, including deep learning, generative AI, NLP, computer vision, and multimodal systems, with hands-on implementation experience.
- Model Evaluation & Optimization: Strong experience evaluating model quality and system-level tradeoffs across accuracy, latency, cost, and scalability dimensions.
- Programming Expertise: Proficiency in Python for AI and ML development, including use of modern AI frameworks and tooling.
- Data Engineering & Access: Strong understanding of data storage, retrieval, and processing systems required to support large-scale training and experimentation workflows.
- Requirements & Systems Thinking: Ability to define technical and non-functional requirements that bridge research, engineering, and production concerns.
Considerations for Top Candidates:
- Bachelor's, Master's, or PhD degree in Data Science, Computer Science, Machine Learning, Statistics, Applied Mathematics, Engineering, or a closely related technical field.
- Proven experience building and deploying advanced ML models beyond traditional analytics use cases.
- Extensive proficiency in Python (NumPy, Pandas, PyTorch, LangChain, etc.); ability to write clean, maintainable, production-oriented code and contribute to shared AI infrastructure.
- Strong hands-on experience with generative AI, large language models, deep neural networks, and modern ML frameworks.
- Demonstrated experience designing evaluation frameworks and benchmarks for AI systems.
- Familiarity with AI infrastructure, cloud platforms (AWS, Azure), and scalable experimentation environments.
- Advanced experience with version control, experiment tracking, and collaborative development (e.g., Git-based workflows).
- Experience working in Agile, cross-functional product development environments.
- Prior exposure to industrial, manufacturing, heavy equipment, or complex physical systems is a strong plus, but not required.
Benefits & conditions
Subject to plan eligibility, terms, and guidelines. This is a summary list of benefits.
- Medical, dental, and vision benefits*
- Paid time off plan (Vacation, Holidays, Volunteer, etc.)*
- 401(k) savings plans*
- Health Savings Account (HSA)*
- Flexible Spending Accounts (FSAs)*
- Health Lifestyle Programs*
- Employee Assistance Program*
- Voluntary Benefits and Employee Discounts*
- Career Development*
- Incentive bonus*
- Disability benefits
- Life Insurance
- Parental leave
- Adoption benefits
- Tuition Reimbursement