Senior Data Scientist

Job Description

Job Description

JOB TITLE: Senior Data Scientist
EMPLOYMENT TYPE : Long term Contract; Any candidate has worked and lived in the USA for 3 years. Will need to obtain Public Trust.
LOCATION DETAILS: Woodlawn, MD (5 days per week onsite)
Onsite Interview after 1st round of video.
Feedback within 24 hours of submittal

• NLP, Entity Resolution & Text Processing
• Python Engineering & Data Pipeline Development
• Advanced SQL & Large-Scale Data Management
• Need Excellent communication skills

• 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.

• 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

• 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.

• 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.