Partner with stakeholders to define and deliver AI/analytics use cases, translating business needs into scalable data science solutions
Design and develop machine learning models and analytical approaches to support search, discovery, and insight generation across structured and unstructured data
Build and implement NLP, semantic search, and entity resolution capabilities to enable advanced information retrieval and relationship analysis
Leverage document-based data (e.g., OCR/ICR outputs, metadata, and free text) to extract insights and support downstream analytics and search solutions
Collaborate with data engineers to integrate models into production environments, including Palantir Foundry, Databricks, and AWS-based platforms
Develop model evaluation frameworks, confidence scoring, and explainability approaches to ensure transparency and usability of AI outputs
Support development of analytics, reporting, and dashboards to drive operational insights and decision-making
Operate within an Agile delivery model, contributing to sprint planning, experimentation, and iterative solution delivery
Communicate findings and recommendations clearly to both technical and non-technical audiences, including client stakeholders.

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field
A minimum of 4 years of experience in data science, machine learning, or applied analytics roles
U.S. Citizenship required and ability to obtain and maintain a Public Trust clearance
Experience developing and applying machine learning models, including: Natural Language Processing (NLP), Semantic search or information retrieval, Entity resolution or relationship modeling
Experience working with large-scale structured and unstructured data, particularly document-based datasets (e.g., text, PDFs, images)
Strong proficiency in Python for data science and machine learning (e.g., Pandas, Scikit-learn, PyTorch or TensorFlow) and solid SQL skills
Experience working with Databricks and/or Spark-based environments for scalable data processing
Familiarity with AWS cloud services for data access, processing, or model deployment
Experience with data lake or lakehouse architectures (e.g., AWS S3, Databricks), including querying and transforming large-scale datasets
Strong communication skills and ability to translate analytical outputs into actionable insights.

Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Position may be eligible for a discretionary variable incentive bonus
Parental Leave and Adoption Assistance
401(k) Retirement Plan
Basic Life & Supplemental Life
Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
Short-Term & Long-Term Disability
Student Loan PayDown
Tuition Reimbursement, Personal Development & Learning Opportunities
Skills Development & Certifications
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Emergency Back-Up Childcare Program
Mobility Stipend

AI/ML Data Scientist

Key skills