Principal AI Data Scientist

HP•Fore Store, VA

About The Position

Leads organization-wide team or teams of other data science professionals in complex projects to create GenAI-based models and digital products. Develops monitoring metrics to reflect real-world model performance and makes recommendations to shape the future direction of models and digital solutions. Manages relationships with senior business partners to evaluate and foster data driven innovation, provides domain-specific expertise in cross-organization projects/initiatives. Ties insights into effective visualizations communicating business value and innovation potential. Works with development teams and business units to ensure models are scalable and can be implemented as part of the delivered solution. Leads project team(s) of data science professionals, assuring insights are communicated regularly and effectively, reviewing designs, models and data compliance. Represents the data science team for all phases of larger and more-complex development projects. Provides guidance, training and mentoring to less experienced staff members. PhD related to AI and 5+ years of experience or Master's degree related to AI and 10+ years of experience. Relevant experience must involve Generative AI and related technologies including machine learning. data analytics, and statistical modeling. Strong foundation in data science and core machine learning concepts. Experience with large language models, multi-modal modals, prompt engineering, vector databases, Retrieval-Augmented Generation (RAG), and search engines. Solid technical background. Experience working on software development teams, especially in cloud-based business applications, is a strong plus. Familiarity with tools such as Azure Machine Learning, Azure Prompt Flow, Python, LangChain, Streamlit, and Docker. Experience working in distributed, diverse teams, with bonus points for time spent in small fast-paced start-ups. Comfortable representing the team in meetings with multiple stakeholders and driving discussions clearly and respectfully. Mastery of English is required. Able to explain technical concepts (e.g., LLMs) to non-technical audiences. You suggest pragmatic solutions that are as simple as possible—even if that means no AI is required. Effective Communication Results Orientation Learning Agility Digital Fluency Customer Centricity The base pay range for this role is $147,050 to $230,850 annually with additional opportunities for pay in the form of bonus and/or equity (applies to US candidates only). Pay varies by work location, job-related knowledge, skills, and experience.

Requirements

PhD related to AI and 5+ years of experience or Master's degree related to AI and 10+ years of experience.
Relevant experience must involve Generative AI and related technologies including machine learning. data analytics, and statistical modeling.
Strong foundation in data science and core machine learning concepts.
Experience with large language models, multi-modal modals, prompt engineering, vector databases, Retrieval-Augmented Generation (RAG), and search engines.
Solid technical background.
Mastery of English is required.
Able to explain technical concepts (e.g., LLMs) to non-technical audiences.
Effective Communication
Results Orientation
Learning Agility
Digital Fluency
Customer Centricity

Nice To Haves

Experience working on software development teams, especially in cloud-based business applications, is a strong plus.
Familiarity with tools such as Azure Machine Learning, Azure Prompt Flow, Python, LangChain, Streamlit, and Docker.
Experience working in distributed, diverse teams, with bonus points for time spent in small fast-paced start-ups.
Comfortable representing the team in meetings with multiple stakeholders and driving discussions clearly and respectfully.
You suggest pragmatic solutions that are as simple as possible—even if that means no AI is required.

Responsibilities

Leads organization-wide team or teams of other data science professionals in complex projects to create GenAI-based models and digital products.
Develops monitoring metrics to reflect real-world model performance and makes recommendations to shape the future direction of models and digital solutions.
Manages relationships with senior business partners to evaluate and foster data driven innovation, provides domain-specific expertise in cross-organization projects/initiatives.
Ties insights into effective visualizations communicating business value and innovation potential.
Works with development teams and business units to ensure models are scalable and can be implemented as part of the delivered solution.
Leads project team(s) of data science professionals, assuring insights are communicated regularly and effectively, reviewing designs, models and data compliance.
Represents the data science team for all phases of larger and more-complex development projects.
Provides guidance, training and mentoring to less experienced staff members.