Senior Data Scientist

• • Selected candidate must be able to obtain and maintain a public trust clearance • • • • Selected candidate must be willing to work on-site in Woodlawn, MD 5 days a week • • ACCEPTING LOCALS only • • Master's and 10+ years of experience, Bachelor's and 12+ years of experience or 18+ years in lieu of a degree • • Key Required Skills • Solid Experience with Natural Language Processing (NLP), Python, NLP frameworks, SQL, Pandas, NLTK and SPACy. • Experience with Generative AI and Large Language Models (LLM) • Excellent Communication skills Position Description • Hands on experience in Python, NLP frameworks, SQL, Pandas, NLTK, SPACy and LLMs • Well versed in SQL and analyzing trends and transactional data. • Understand real world challenges and develop automated data solutions • Develop, test, and deploy new techniques for NLP understanding • Scalable development/deployment of ML and Generative AI approaches (such as Large Language Models (LLMs) • Train and optimize NLP/LLM models and create Python based pipelines • Experience building cloud native solutions on AWS • Determine the nature of analytic problems, evaluate options, and offer recommendations for resolution. • Advise on the methods and data needed and/or available to evaluate the (intelligence or data) problem. • Collaborate with data collectors and analysts to identify and close gaps on complex monitoring problems. • Provide accurate, timely, complex, and sophisticated data analysis. Skills Requirements • Bachelor’s degree in Statistics, Applied Mathematics, Computer Science, or Information Science with industry experience on Python, NLP frameworks, SQL, Pandas, NLTK and SPACy, data science, and AI/ML/LLM engineering. • 15 year s+candidate • Solid Experience with Natural Language Processing (NLP), Python, NLP frameworks, SQL, Pandas, NLTK and SPACy. • Experience with Generative AI and Large Language Models (LLM) • Evidence of true self-starter and operating independently. • Fluency in Python Programming, version control and collaboration with GIT, standard Python packages (ex. Pandas, numpy, matplotlib) and ML frameworks • Knowledge of TensorFlow, PyTorch, Pandas, scikit-learn, NLTK, Azure ML (optional), Amazon Web Services EC2. • Experience with scalable data engineering frameworks such as Apache Spark and orchestration frameworks such as Airflow, and/or experience with semantic search. • Expert knowledge in conducting data analysis and applying advanced statistical concepts and ML methods to build, train, test, and evaluate a variety of supervised and unsupervised analytic models. • Experience with ML model deployment and operations like DevOps, MLOps, LLMOps. • Experience with NLP and Generative AI libraries like regular expressions (e.g., spacy, langchain), text annotation tools and semantic frameworks. • Ability to clean and process large amounts of real-world data. • Experience retrieving and manipulating data from a variety of data sources included DB2, Oracle, SQL Server, Hadoop and flat files. • Excellent Communication skills. • Experience with database management systems (e.g., PostgresSQL, MySQL, SQLite, SQL, etc.) • Excellent analytical skills to identify potential risks and propose effective solutions. • Excellent problem-solving skills, ability to collaborate with cross-functional teams and proven communication in written and verbal formats to various audiences to include executive leadership. • Prior experience with federal or state governments IT projects. • Industry experience preferred • Experience with, or the ability and willingness to learn distributed processing via the Hadoop ecosystem, i.e., Spark, Impala and Hive. • Experience working in an analytical research environment. • Experience in parallel processing such as GPU programming with CUDA • Experience with Mathematica • Experience using markup languages such as LaTeX, HTML, etc. • Experience with Natural Language Processing for anomaly detection.