Onsite Senior Data Scientist

• 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.

• 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.

· Overall 10+ years' experience in IT industry

· 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