Data Scientist
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Role details
Tech stack
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Job description
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Apply hands-on experience in Python, NLP frameworks, SQL, Pandas, NLTK, and spaCy to solve real-world data challenges
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Analyze trends and transactional data using strong SQL skills
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Develop, test, and deploy new techniques for NLP understanding
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Build scalable ML and Generative AI solutions, including Large Language Models (LLMs)
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Train and optimize NLP/LLM models and build Python-based data pipelines
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Build cloud-native solutions on AWS
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Determine the nature of analytic problems, evaluate options, and recommend resolutions
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Advise on methods and data needed to evaluate complex data problems
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Collaborate with data collectors and analysts to close gaps on complex monitoring problems
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Deliver accurate, timely, and sophisticated data analysis
Requirements
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., * 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
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10+ years overall IT industry experience
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Education/experience combinations accepted: Master’’s + 10 years; Bachelor’’s + 12 years; or 18 years in lieu of a degree
Required Skills
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Solid experience with NLP, Python, NLP frameworks, SQL, Pandas, NLTK, and spaCy
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Experience with Generative AI and LLMs
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Demonstrated self-starter, able to operate independently
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Fluency in Python, version control/Git, standard Python packages (Pandas, NumPy, Matplotlib), and ML frameworks
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Knowledge of TensorFlow, PyTorch, Pandas, scikit-learn, NLTK, AWS EC2 (Azure ML a plus)
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Experience with scalable data engineering frameworks (e.g., Apache Spark) and orchestration frameworks (e.g., Airflow), and/or semantic search
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Expert-level data analysis and advanced statistical/ML methods to build, train, test, and evaluate supervised and unsupervised models
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Experience with ML model deployment and operations (DevOps, MLOps, LLMOps)
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Experience with NLP/Generative AI libraries (e.g., spaCy, LangChain), text annotation tools, and semantic frameworks
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Ability to clean and process large volumes of real-world data
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Experience retrieving/manipulating data from varied sources (DB2, Oracle, SQL Server, Hadoop, flat files)
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Experience with database management systems (PostgreSQL, MySQL, SQLite, SQL, etc.)
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Excellent analytical and problem-solving skills; ability to identify risks and propose solutions
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Excellent written and verbal communication skills across audiences, including executive leadership
Desired Skills
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Prior experience on federal or state government IT projects
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Industry experience strongly preferred
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Experience with, or willingness to learn, the Hadoop ecosystem (Spark, Impala, Hive)
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Experience in an analytical research environment
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Experience in parallel/GPU processing (CUDA)
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Experience with Mathematica
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Experience with markup languages (LaTeX, HTML)
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Experience with NLP for anomaly detection
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