AI Data Scientist – Enterprise AI

AI Data Scientist – Enterprise AI

The Enterprise Operations Applied AI organization is seeking an AI Data Scientist to help design, build, evaluate, and scale AI‑driven solutions that deliver measurable business impact across enterprise operations. This role sits at the intersection of applied research, machine learning engineering, data science, and business transformation. It requires strong technical expertise in Large Language Models (LLMs), Generative AI, machine learning, and large‑scale data analysis combined with effective collaboration across multidisciplinary teams.

• Design, develop, and deploy AI‑powered solutions leveraging Large Language Models (LLMs), Generative AI technologies, machine learning, and predictive analytics.
• Develop data pipelines, feature engineering approaches, and analytical workflows that support AI solution development.
• Research new AI methods, tools, and frameworks and determine their applicability to business problems across enterprise operations.
• Design and execute experiments to evaluate model effectiveness, accuracy, robustness, and operational performance.
• Analyze large‑scale structured and semi‑structured datasets to generate insights, build predictive models, and support operational decision‑making.
• Translate business requirements into technical approaches and clearly communicate AI concepts to both technical and non‑technical audiences.
• Support adoption of AI solutions through training, demonstrations, documentation, and stakeholder engagement.
• Collaborate with distributed teams of engineers, data scientists, product owners, business leaders, and technology organizations to deliver impactful solutions.
• Contribute to AI best practices, reusable frameworks, and technical standards across the organization.

• Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Engineering, Mathematics, or a related field.
• 3+ years of experience developing AI, machine learning, and data science solutions.
• Proficiency in Python and modern AI/ML libraries and frameworks.
• Experience with model evaluation, experimentation, performance measurement, and validation methodologies.
• Strong analytical skills with experience working with large‑scale tabular datasets using SQL, Spark, Databricks, or similar technologies.
• Ability to collaborate effectively in culturally diverse and distributed teams.

• 5+ years of experience developing AI, machine learning, and data science solutions in an industry setting.
• Experience developing AI solutions in cloud environments such as Azure, AWS, or GCP.
• Proficiency in software development tools such as version control (e.g., Git Hub) and AI‑assisted development tools (e.g., Git Hub Copilot).
• Experience with Retrieval‑Augmented Generation (RAG), prompt engineering, and AI agents.
• Familiarity with MLOps, model monitoring, observability, and enterprise AI governance concepts.
• Experience communicating technical concepts to business stakeholders.
• Experience working in highly collaborative, matrixed organizations.

A successful AI Data Scientist – Enterprise AI builds AI solutions that move beyond prototypes and create measurable business value, demonstrates technical depth in LLMs, machine learning, and data science while maintaining a practical focus on implementation, clearly communicates with product managers, engineers, and operational teams, takes ownership of outcomes, proactively drives work forward, and continuously identifies opportunities to improve processes, solutions, and ways of working.

• Applied AI & Machine Learning
• Large Language Models (LLMs) & Generative AI
• Data Science & Statistical Analysis
• Enterprise Problem Solving
• Experimentation & Model Evaluation
• Communication & Storytelling
• Cross‑Functional Collaboration
• Ownership & Accountability

The pay range for this role is $130,700 to $205,200 USD annually with additional opportunities for bonus and/or equity (applicable to United States of America candidates only). Pay varies by work location, job‑related knowledge, skills, and…