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Senior Data Scientist AI Evaluation_Hybrid@Johnston,RI

BURGEON IT SERVICES LLCJohnston, RI🇺🇸United StatesPosted Sep 16, 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Johnston, RI, United States
Posted
19 hours ago
AWSMLflowMachine LearningNumPyScikit-learnDatabricksGenerative AILLMPandasPython

Job Description

Role: Senior Data Scientist Generative AI / Conversational AI Evaluation
Location: Johnston, RI or Westwood, MA

Hybrid/Onsite preferred, though location flexibility may be considered

Domain: Cards, Banking, FSI

Description:

We are seeking an experienced Data Scientist to support the development and evaluation of AI-powered fraud self-service voice agents and conversational AI systems. The primary responsibility is not model deployment or engineering implementation, but designing evaluation frameworks, measuring system performance, identifying failure patterns, conducting root-cause analysis, and optimizing model behavior through data-driven experimentation.

Key Responsibilities

  • Design and execute evaluation frameworks for LLM, RAG, and multi-turn conversational AI systems.
  • Develop metrics to assess customer intent recognition, conversation quality, guardrail effectiveness, and business outcomes.
  • Analyze voice-agent interactions and identify areas of failure, drift, and performance degradation.
  • Perform prompt tuning and experimentation to improve model accuracy and reliability.
  • Conduct root-cause analysis of conversational failures and recommend remediation strategies.
  • Measure performance across different model configurations, prompts, and guardrail implementations.
  • Partner with AI Engineering and Product teams to validate solutions before production deployment.
  • Build dashboards and reports that communicate model effectiveness and operational impact.
  • Support fraud-related customer service use cases, including intent detection and multi-turn conversation flows.

Success Criteria

  • Develop reliable evaluation methodologies for conversational AI systems.
  • Quantify the effectiveness of fraud self-service voice agents.
  • Optimize prompts, retrieval strategies, and guardrails using empirical evidence.
  • Deliver actionable insights that improve customer experience and model performance.
  • Establish measurable KPIs for intent detection and multi-turn conversation success.

Mandatory Skills:

  • Strong background in Data Science, Machine Learning, Generative AI, or a related quantitative field.
  • Hands-on experience evaluating LLM, RAG, Agentic AI, or Conversational AI solutions.
  • Deep understanding of model evaluation techniques and metrics, including:
    • Precision@K
    • Recall@K
    • Mean Reciprocal Rank (MRR)
    • F1 Score
    • Retrieval and generation quality assessment
  • Experience performing experimentation, statistical analysis, and performance benchmarking.
  • Strong Python programming skills.
  • Experience with machine learning libraries and frameworks such as Scikit-learn, XGBoost, Pandas, NumPy, and related tools.
  • Ability to communicate technical findings succinctly to highly technical stakeholders.

Desired Skills:

  • Experience with:
    • Generative AI and LLM ecosystems
    • Multi-agent systems
    • RAG/Agentic RAG architectures
    • Amazon Bedrock
    • AWS SageMaker
    • Databricks
    • MLflow
    • LangSmith
    • Weights & Biases
  • Knowledge of conversational AI, IVR systems, digital assistants, and voice agents.
  • Experience in financial services, fraud detection, or customer service automation

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