Senior Data Scientist

• IT IS 100 % On Site position in Woodlawn
  
• 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
  

• Strong practical experience with Natural Language Processing (NLP), Text Processing, and Information Extraction concepts including Named Entity Recognition, Blocking and Indexing, String Distance Metrics, TF-IDF/Cosine Similarity, Phonetics Encoding, Address Standardization
  
• Solid Python, Regex, and SQL experience
  
• Excellent Communication skills
  

• Develop Analytics Solutions: Design, implement, and maintain advanced data processing and entity resolution pipelines using Python and SQL on enterprise data platforms.
  
• Data Hygiene & Management: Clean, transform, and manage large-scale datasets from diverse, complex sources, ensuring absolute data integrity, reliability, and security.
  
• Performance Optimization: Optimize complex SQL queries and database operations to ensure efficient data access, processing, and scalability.
  
• Engineering Standards: Actively participate in code reviews, enforce version control, and uphold best practices for code quality, reproducibility, and data privacy.
  
• End-to-End Delivery: Support data validation, testing, deployment, and post-implementation monitoring in a fast-paced environment.
  

Requirements

BASIC QUALIFICATIONS:

• Master's and 10+ years of experience, Bachelor's and 12+ years of experience or 18+ years in lieu of a degree
  
• Bachelor’s degree in Statistics, Applied Mathematics, Computer Science, or Information Science with experience in NLP, Text Processing, Information Extraction, Python, SQL, Regex and specialized libraries/frameworks.
  
• Overall 10+ years’ experience in IT industry
  

REQUIRED SKILLS:

• Strong practical experience with Natural Language Processing (NLP), Text Processing, and Information Extraction including:
  
• Practical knowledge of Named Entity Recognition and Address Standardization to extract and clean unstructured text data.
  
• Deep understanding of data matching strategies, including Blocking and Indexing, String Distance Metrics, and Phonetic Encoding.
  
• Experience applying TD-IDF and Cosine Similarity for text comparisons and information retrieval.
  
• Strong Python development skills for building analytics solutions and manipulating data.
  
• Advanced SQL proficiency for complex data querying, optimization, and database operations.
  
• Practical experience using Regex for advanced text processing, data cleansing, and pattern matching.
  
• Familiarity with specialized libraries and frameworks including:
  
• Linkage libraries such as Splink / FastLink, Dedupe, or recordlinkage
  
• Core Python data science libraries, specifically spaCy for NLP tasks and Scikit-Learn for general machine learning and clustering
  
• Familiarity with code reviews, version control, and maintaining data security and reproducibility standards.
  
• Excellent communication skills.
  

DESIRED SKILLS:

• Prior experience delivering IT or data initiatives within federal, state, or local government environments
  
• Proven ability to operate independently, take ownership of data pipeline architectures, and drive projects from data discovery through to post-implementation.
  
• Experience retrieving, migrating, and manipulating data from legacy and distributed systems, including PostgreSQL, DB2, Oracle, SQL Server, and Hadoop, as well as unstructured flat files.
  
• Experience utilizing Jenkins to automate continuous integration, testing, and deployment (CI/CD) for data validation pipelines.
  
• Experience with pipeline automation tools to schedule and monitor complex data cleansing jobs.
  
• Strong ability to translate complex algorithmic decisions (such as probabilistic match thresholds) into clear business logic for executive leadership and non-technical stakeholders.
  
• Excellent problem-solving skills and proven verbal/written communication skills when collaborating across cross-functional teams.