Location: On-site 5 days/week — local candidates only, ready to interview immediately
Clearance: Must be able to obtain and maintain a Public Trust clearance
We are seeking a Senior Data Scientist with deep, hands-on expertise in Natural Language Processing (NLP) and Generative AI/LLMs to support a federal data science initiative. The ideal candidate is a true self-starter who can operate independently, translate complex analytic problems into automated data solutions, and communicate findings clearly to both technical teams and executive leadership.
- Apply hands-on experience in Python, NLP frameworks, SQL, Pandas, NLTK, and spaCy to solve real-world data challenges
- Analyze trends and transactional data using strong SQL skills
- Develop, test, and deploy new techniques for NLP understanding
- Build scalable ML and Generative AI solutions, including Large Language Models (LLMs)
- Train and optimize NLP/LLM models and build Python-based data pipelines
- Build cloud-native solutions on AWS
- Determine the nature of analytic problems, evaluate options, and recommend resolutions
- Advise on methods and data needed to evaluate complex data problems
- Collaborate with data collectors and analysts to close gaps on complex monitoring problems
- Deliver accurate, timely, and sophisticated data analysis
- Bachelor's degree in Statistics, Applied Mathematics, Computer Science, or Information Science, with industry experience in Python, NLP frameworks, SQL, Pandas, NLTK, spaCy, data science, and AI/ML/LLM engineering
- 10+ years overall IT industry experience
- Education/experience combinations accepted: Master's + 10 years; Bachelor's + 12 years; or 18 years in lieu of a degree
- Solid experience with NLP, Python, NLP frameworks, SQL, Pandas, NLTK, and spaCy
- Experience with Generative AI and LLMs
- Demonstrated self-starter, able to operate independently
- Fluency in Python, version control/Git, standard Python packages (Pandas, NumPy, Matplotlib), and ML frameworks
- Knowledge of TensorFlow, PyTorch, Pandas, scikit-learn, NLTK, AWS EC2 (Azure ML a plus)
- Experience with scalable data engineering frameworks (e.g., Apache Spark) and orchestration frameworks (e.g., Airflow), and/or semantic search
- Expert-level data analysis and advanced statistical/ML methods to build, train, test, and evaluate supervised and unsupervised models
- Experience with ML model deployment and operations (DevOps, MLOps, LLMOps)
- Experience with NLP/Generative AI libraries (e.g., spaCy, LangChain), text annotation tools, and semantic frameworks
- Ability to clean and process large volumes of real-world data
- Experience retrieving/manipulating data from varied sources (DB2, Oracle, SQL Server, Hadoop, flat files)
- Experience with database management systems (PostgreSQL, MySQL, SQLite, SQL, etc.)
- Excellent analytical and problem-solving skills; ability to identify risks and propose solutions
- Excellent written and verbal communication skills across audiences, including executive leadership
- Prior experience on federal or state government IT projects
- Industry experience strongly preferred
- Experience with, or willingness to learn, the Hadoop ecosystem (Spark, Impala, Hive)
- Experience in an analytical research environment
- Experience in parallel/GPU processing (CUDA)
- Experience with Mathematica
- Experience with markup languages (LaTeX, HTML)
- Experience with NLP for anomaly detection
