Principal Data Scientist

Summary

Join Rackner as a Principal Data Science to architect advanced machine learning solutions and lead the strategic implementation of cutting-edge AI technologies, focusing on AI and LLMs. You will support the FDA, working at the forefront of regulatory science and technology. This leadership role blends deep technical expertise with strategic vision, enabling you to drive innovation, mentor team members, and shape how organizations approach critical data science challenges. The position involves developing AI/ML models for regulatory documents, collaborating with FDA experts, implementing data pipelines, optimizing model performance, and ensuring compliance with FDA regulations. You will also deliver client presentations, identify innovation opportunities, and lead LLM development initiatives.

Requirements

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field
• 7–8 years of professional experience in data science or analytics, with leadership exposure
• 2–3 years of hands-on experience with LLMs (e.g., fine-tuning, prompt engineering, instruction tuning)
• Ability to obtain a Public Trust Clearance (required)
• Authorization to work in the United States
• Strong proficiency in Python (preferred) and experience with other languages such as C, R, Java, or Scala
• Expertise in statistical modeling, machine learning, NLP, and deep learning techniques
• Familiarity with AWS services: Athena, S3, Glue, SageMaker, Comprehend, Bedrock

Responsibilities

• Architect and develop AI/ML models for analyzing regulatory documents
• Collaborate with FDA subject matter experts to validate models and ensure relevance for regulatory decision-making
• Implement data preprocessing and feature engineering pipelines for unstructured data
• Optimize model performance with a focus on accuracy, efficiency, and scalability
• Ensure compliance with FDA Good Machine Learning Practices (GMLP) and regulatory requirements
• Conduct predictive modeling, optimization, and continuous model monitoring
• Deliver client-facing presentations to executive stakeholders
• Identify new opportunities for innovation and strategic AI/ML initiatives
• Lead initiatives focused on LLM development, including fine-tuning, evaluation, and deployment strategies

Preferred Qualifications

• Exposure to MLOps practices, big data technologies (Hadoop, Spark), and cloud platforms
• PEFT (e.g., LoRA/QLoRA) for efficient fine-tuning
• Instruction fine-tuning, Retrieval-Augmented Generation (RAG), Chain-of-Thought (CoT) or Tree-of-Thought (ToT) prompting
• Quantization, pruning, and knowledge distillation techniques
• Experience with Hugging Face Transformers, LangChain, Llama Index, or large-scale training frameworks
• Familiarity with LLM evaluation metrics, model interpretability, and optimization best practices
• Exceptional written and verbal communication skills
• Strong problem-solving abilities and passion for continuous learning
• Collaborative, team-oriented mindset with the ability to partner with diverse stakeholders

Benefits

• 401(k) with 100% company match up to 6%
• Highly competitive Paid Time Off (PTO)
• Comprehensive health insurance (Medical, Dental, Vision) with a broad provider network
• Life Insurance and Short- & Long-Term Disability coverage
• Industry-leading weekly pay schedule
• Home office and equipment reimbursement plan
• Fitness/Gym membership eligibility
• Employee swag, snacks, and company events