Kforce is searching for a Mid-Level Data Scientist to join our client project team at the forefront leveraging advanced AI and machine learning techniques to solve complex problems. We are looking for a talented Data Scientist with a strong focus on Natural Language Processing (NLP) and Natural Language Understanding (NLU) to join our dynamic team. This is a remote position.
Responsibilities:
Apply NLP/NLU techniques to analyze and process unstructured data, including PDF documents
Process large and complex documents containing diverse content types such as text, tables, plots/graphs, photos, and diagrams
Partition large documents, detect and classify document elements, recognize and extract text/OCR, and extract and disambiguate named entities
Extract and transpose table data, recognize and classify images, analyze the layout of different elements, and infer relationships between elements based on page positioning
Apply generative AI (large foundational models) to document processing, content understanding, summarization, entity extraction, data analysis, image interpretation, and question answering
Fine-tune pre-trained large language models (LLMs) for specific tasks
Implement search and retrieval techniques for large collections of documents with diverse content types
Utilize traditional NLP models like LayoutLM
Train, develop, tune, and evaluate AI/ML models to ensure accuracy and efficiency
Develop production-grade data pipelines to process large volumes of documents in batch or near-real-time, ensuring scalability through distributed and parallel processing frameworks
Implement AI pipelines with Humans in the Loop (HITL), including labeling and validation processes
Evaluate models using metrics relevant to document processing tasks (e.g., NER metrics, binary classification metrics)
Ensure compliance with strict security requirements and the ability to perform tasks in air-gapped environments
REQUIREMENTS:
Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field
3-5 years of experience in NLP/NLU and machine learning
Experience with NLP libraries and frameworks (e.g., spaCy, NLTK, Hugging Face Transformers)
Experience with distributed processing frameworks (e.g., Apache Spark, Hadoop)
Proficiency in programming languages such as Python, R, or Java
Strong understanding of AI/ML model development, tuning, and evaluation
Familiarity with model evaluation metrics and techniques
Excellent problem-solving skills and attention to detail
Strong communication and teamwork abilities
Preferred Qualifications:
Experience with generative AI models and fine-tuning LLMs
Knowledge of search and retrieval techniques for large document collections
Experience with production-grade data pipeline development
Familiarity with HITL processes and validation techniques
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless
and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
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