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 other 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 (preferred).
Experience developing AI solutions in cloud environments such as Azure, AWS, or GCP (preferred).
Proficiency using software development tools such as version control (e.g. Github) and AI-assisted development tools (e.g. Github Copilot) (preferred).
Experience with Retrieval-Augmented Generation (RAG), prompt engineering, AI agents (preferred).
Familiarity with MLOps, model monitoring, observability, and enterprise AI governance concepts (preferred).
Experience communicating technical concepts to business stakeholders (preferred).
Experience working in highly collaborative, matrixed organizations (preferred).

Health insurance
Dental insurance
Vision insurance
Long term/short term disability insurance
Employee assistance program
Flexible spending account
Life insurance
Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure
11 paid holidays
Additional flexible paid vacation and sick leave

AI Data Scientist – Enterprise AI

Key skills