Senior Data Scientist

Candidates need to have excellent communication skills. This will be 5 days working from SSA HQ, so candidates should be local and ready to interview immediately

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

• 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.

  • Skills Requirements:

    Foundation for Success (Basic Qualifications)

    • 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

      Factors To Help You Shine (Required Skills)

      **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**
      **Master''s and 10+ years of experience, Bachelor''s and 12+ years of experience or 18+ years in lieu of a degree**

      • 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.

        How To Stand Out From The Crowd (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