Senior Data Scientist at iQuasar LLC in AL-Fort Rucker-36362 Fully Remote - US

Job description

• One of our clients in Reston, VA needs a Data Scientist for a permanent position.

Responsibilities

• 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.

Requirements

• Minimum 8 years of hands-on experience in AI/ML software development using Python and R.
• Strong background in deep learning, transformer-based NLP, and classical ML.
• Experience with RAG, LLMs, and embedding-based retrieval systems.
• Expertise in data wrangling, Web scrapping, data standardization, and feature engineering.
• Proven experience working with vector databases (e.g., FAISS, Pinecone, Weaviate) or graph databases (e.g., Neo4j).
• Strong understanding of ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Familiarity with version control systems (e.g., Git, GitHub).
• Experience with cloud computing platforms (AWS, GCP, or Azure).
• Demonstrated ability to produce high-quality technical documentation and research publications.
• Master’s degree or Ph.D. in Statistics, Computer Science, or a related quantitative discipline.
• Hands-on experience with SAS, SQL, Amazon RDS, and JIRA.
• Knowledge of ML Ops practices and model deployment pipelines.
• Prior experience in contributing to academic or technical publications.
• Exposure to federal or enterprise-scale projects is a plus.

Skills

Required

• Python
• R
• Deep learning
• Transformer-based NLP
• Classical ML
• RAG
• LLMs
• Embedding-based retrieval systems
• Data wrangling
• Web scraping
• Data standardization
• Feature engineering

Preferred

• SAS
• SQL
• Amazon RDS
• JIRA
• ML Ops
• Model deployment pipelines
• Academic or technical publications
• Federal or enterprise-scale projects