Senior Data Scientist[Remote]- W2 Role

Senior Data Scientist II
Position: Senior Data Scientist II
Location: Remote (EST) — Hybrid in Raleigh, NC preferred
Rate Type: BH W2
Duration: 6 months, with possible extension/conversion
Interview Process: 2 rounds via video

Position Overview

LexisNexis is seeking experienced Senior Data Scientist II professionals to develop innovative, customer-facing data science and AI solutions. The ideal candidate will have strong expertise in modern data science, Generative AI, LLMs, RAG, agentic AI, unstructured data, and production machine learning.

You will work closely with Machine Learning Engineers (MLEs) and cross-functional teams throughout the product development and production lifecycle, turning complex data into scalable, customer-focused solutions.

Required Qualifications

• 8 years of total professional experience in data science, machine learning, or a closely related field.
• 5 years of recent Data Science experience, with hands-on expertise in areas such as:
  • MCP
  • RAG implementations, evaluations, validations, and proof-of-concepts
  • Agentic AI
  • Generative AI
  • LLM applications
  • Unstructured data
• Proven experience building customer-facing data science or AI products.
• Experience partnering with Machine Learning Engineers (MLEs) throughout the production lifecycle.
• Strong Python programming skills.
• Strong understanding of machine learning algorithms, including:
  • Deep Learning
  • Gradient Boosting
  • Random Forests
• Experience working directly with Large Language Models (LLMs) and Transformer-based architectures, including:
  • BERT
  • RoBERTa
  • T5
• Hands-on experience applying LLM technologies such as:
  • ChatGPT
  • GPT-3.5
  • Claude
  • Mistral
• Experience working with large datasets and distributed computing systems, such as Hadoop and Spark.

Preferred Qualifications

• Experience working within large enterprise environments.
• Experience taking AI/ML solutions from experimentation and proof-of-concept through production.
• Strong understanding of modern Generative AI and LLM ecosystem.
• Experience working with cross-functional teams to deliver business and customer-focused solutions.

Key Responsibilities

• Develop advanced data science and AI solutions using complex datasets.
• Design, implement, evaluate, and validate RAG, agentic AI, MCP, and Generative AI solutions.
• Work with unstructured data to extract meaningful insights and develop innovative AI applications.
• Apply machine learning and deep learning techniques to solve complex business problems.
• Work directly with LLMs and Transformer-based architectures.
• Collaborate closely with MLEs to move models and AI solutions into production.
• Contribute to the full product lifecycle, from research and experimentation through deployment and optimization.
• Analyze large-scale datasets using distributed computing technologies such as Spark and Hadoop.
• Partner with cross-functional teams to translate business requirements into data-driven solutions.
• Drive actionable insights that support business strategy, customer experience, and product growth.
• Stay current with emerging developments in Generative AI, LLMs, machine learning, and AI engineering.

Ideal Candidate

The ideal candidate is a senior-level Data Scientist with strong hands-on Generative AI/LLM experience, particularly someone who has recently worked on RAG, MCP, agentic AI, unstructured data, and customer-facing AI products and has experience taking solutions into production.

Must-Have Keywords:
Python | Data Science | Generative AI | LLM | RAG | MCP | Agentic AI | Unstructured Data | Machine Learning | Deep Learning | Transformers | BERT | RoBERTa | T5 | Spark | Hadoop | Customer-Facing Products | MLE Collaboration