Senior Data Scientist

PLEASE NOTE:

• It is 100% onsite position in Woodlawn MD.
  
• Candidate must be able to obtain and maintain a public trust clearance
  
• Candidate must be willing to work 5 days a week
  

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.
  

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.

Requirements

Skills Requirements:

Basic Qualification:

• Masters and 10 years of experience Bachelors and 12 years of experience or 18 years in lieu of a degree
  
• Bachelors 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
  

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)
  
• 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.
  

Desired Skills:

• 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.