Senior Data Scientist

What you'll work on

• Lead development of predictive models using deep learning and classical machine learning algorithms.
• Build and optimize NLP models leveraging transformer-based architectures (e.g., BERT, GPT).
• Design and implement Retrieval-Augmented Generation (RAG) approaches for LLM-based applications.
• Work with vector databases and graph databases for knowledge representation and retrieval.
• Generate and use simulated data to support training and testing of ML models.
• Perform data standardization, aggregation, and integration from structured and unstructured sources.
• Collaborate with cross-functional teams to understand business needs and translate them into ML solutions.
• Document workflows, produce technical reports, and contribute to academic or industry publications.
• Use version control tools to manage collaborative model development (e.g., GitHub).
• Support end-to-end ML lifecycle from data wrangling and modeling to deployment and monitoring.

What we're looking for

• Hands-on experience with SAS, SQL, Amazon RDS, and JIRA.
• Knowledge of MLOps practices and model deployment pipelines.
• Prior experience in contributing to academic or technical publications.
• Exposure to federal or enterprise-scale projects is a plus.

Job Type: Full-time

Pay: $160,000.00 - $175,000.00 per year

Benefits:

• 401(k)
• Dental insurance
• Health insurance
• Paid time off
• Vision insurance

Education:

• Master's (Preferred)

Experience:

• Python: 6 years (Required)
• R: 6 years (Required)
• Machine learning: 6 years (Required)
• Vector Database: 4 years (Required)
• AWS: 5 years (Required)
• SQL: 5 years (Required)

Work Location: In person