Senior Data Scientist

Senior Data Scientist - Immediate Hire Location: Woodlawn, MD (Onsite – 5 Days/Week) - Candidates willing to relocate and work onsite are welcome to apply Clearance Requirement: Selected candidate must be able to obtain and maintain a Public Trust Clearance. Work Authorization & Additional Requirements • Selected candidate must be able to obtain and maintain a Public Trust Clearance. • Selected candidate must be willing to work onsite in Woodlawn, MD, five (5) days per week. • We are considering only W2 or 1099 candidates for this position. Candidates represented through third-party employers/vendors on C2C will not be considered. • Candidates must possess a valid U.S. government-issued REAL ID-compliant driver's license or an acceptable REAL ID-compliant identification document, as identity verification is required for this Federal project. Position Overview We are seeking an experienced Senior Data Scientist with strong expertise in Natural Language Processing (NLP), Machine Learning, Generative AI, and Large Language Models (LLMs). The ideal candidate will have extensive hands-on experience developing scalable AI/ML solutions using Python and modern NLP frameworks while working with large, real-world datasets. This role requires a highly motivated self-starter who can independently analyze complex business problems, build intelligent data solutions, collaborate with cross-functional teams, and deploy cloud-native AI applications on AWS. Key Responsibilities • Design, develop, test, and deploy NLP and Machine Learning solutions using Python. • Develop scalable Generative AI and Large Language Model (LLM) applications. • Train, fine-tune, optimize, and evaluate NLP and LLM models. • Build robust Python-based data processing and inference pipelines. • Analyze large transactional and structured datasets using SQL and Python. • Understand real-world business challenges and develop automated data-driven solutions. • Develop cloud-native AI/ML solutions on AWS. • Implement scalable ML pipelines and model deployment using MLOps/LLMOps best practices. • Perform advanced statistical analysis and build supervised and unsupervised machine learning models. • Retrieve, clean, transform, and process large volumes of data from multiple enterprise data sources. • Collaborate with analysts, engineers, and stakeholders to identify data gaps and recommend effective solutions. • Present analytical findings and technical recommendations to leadership and business stakeholders. • Maintain source code using Git and follow software development best practices. Required Qualifications • Master's degree with 10+ years of experience, Bachelor's degree with 12+ years of experience, or 18+ years of relevant experience in lieu of a degree. • Overall 10+ years of IT industry experience. • Bachelor's or Master's degree in Computer Science, Information Science, Statistics, Applied Mathematics, Data Science, or a related field. Required Technical Skills Programming & Data Analysis • Python • SQL • Pandas • NumPy • Matplotlib • Git Natural Language Processing • Natural Language Processing (NLP) • NLTK • spaCy • Regular Expressions • Text Annotation Tools • Semantic Frameworks AI / Machine Learning • Generative AI • Large Language Models (LLMs) • TensorFlow • PyTorch • Scikit-learn • Supervised & Unsupervised Machine Learning • Model Training, Evaluation & Optimization ML Deployment • MLOps • LLMOps • DevOps • Python Pipelines Cloud & Data Engineering • Amazon Web Services (AWS) • Amazon EC2 • Apache Spark • Apache Airflow • Semantic Search Databases • SQL Server • Oracle • DB2 • PostgreSQL • MySQL • SQLite • Hadoop • Flat Files Required Soft Skills • Excellent verbal and written communication skills. • Strong analytical and problem-solving abilities. • Ability to work independently with minimal supervision. • Strong collaboration skills with cross-functional teams. • Ability to analyze complex datasets and provide actionable recommendations. • Experience communicating technical findings to executive leadership. Preferred Qualifications • Experience supporting Federal or State Government IT projects. • Industry experience in Data Science or Artificial Intelligence. • Experience with the Hadoop ecosystem, including Spark, Hive, and Impala. • Experience working in an analytical research environment. • Experience with GPU programming using CUDA. • Experience with Mathematica. • Experience using markup languages such as HTML and LaTeX. • Experience applying NLP techniques for anomaly detection. • Experience with Azure ML.