Data Scientist – NLP / Generative AI

BizFirst•Alexandria, VA

136d•Hybrid

About The Position

BizFirst is assisting our client with the hiring of a Data Scientist specializing in natural language processing and generative AI to help the organization move from early experimentation into production-ready AI capabilities. This is a hands-on research and engineering role where you will own the design and delivery of NLP and GenAI solutions applied directly to the client’s most complex internal workflows. Our client is a mid-market professional services organization that is actively rethinking how it designs and executes its core business operations through artificial intelligence and automation. The company is building a dedicated AI capability to embed machine learning and generative AI into its most critical internal workflows – from decision support and process automation to real-time analytics and intelligent document processing.

Requirements

US Citizen or Permanent Resident authorized to work in the United States.
Experience: 5–8 years of applied data science experience with a strong focus on natural language processing and text-based systems.
NLP & GenAI: Hands-on experience with transformer architectures (BERT, GPT, T5, or similar), fine-tuning workflows, and production deployment of language models.
RAG & Embeddings: Direct experience building retrieval-augmented generation pipelines, vector databases (Pinecone, Weaviate, FAISS, or equivalent), and semantic search systems.
Programming: Strong Python skills; proficiency with HuggingFace Transformers, LangChain, or similar GenAI tooling.
Evaluation: Experience designing rigorous evaluation frameworks for generative models, including human evaluation, LLM-as-judge approaches, and automated benchmarking.

Nice To Haves

Experience applying NLP in a professional services, legal, finance, or consulting domain.
Familiarity with responsible AI practices, including bias assessment, output auditing, and hallucination mitigation.
Background in information extraction, named entity recognition (NER), or document intelligence.
Experience with cloud-based GenAI services (OpenAI API, Anthropic API, AWS Bedrock, Azure OpenAI, or GCP Vertex AI).
Graduate degree (MS or PhD) in Computer Science, Computational Linguistics, Statistics, or a related field.

Responsibilities

Design and build NLP and generative AI solutions applied to internal business processes, including document understanding, classification, summarization, and conversational AI.
Develop, fine-tune, and evaluate large language models and transformer-based architectures for domain-specific applications.
Build and iterate on retrieval-augmented generation (RAG) systems, embedding pipelines, and vector search infrastructure.
Work closely with business and operations stakeholders to scope problems, define evaluation criteria, and validate model outputs against real-world requirements.
Analyze and interpret model behavior, identify failure modes, and develop mitigation strategies to ensure reliable, responsible outputs.
Collaborate with ML engineers and platform teams to move experiments into production pipelines.
Document experimental methodology, data lineage, and model evaluations to support reproducibility and knowledge sharing.
Stay current on developments in NLP research and GenAI tooling, bringing relevant advances into the team’s work quickly.