Senior Banking AI Scientist - Conversational NLP and GenAI

Fractal Analytics Inc.

New York (NY)

On-site

USD 110,000 - 140,000

Full time

14 days+

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Job summary

Fractal Analytics Inc. is seeking a hands-on Senior Data Scientist to design and deliver agentic conversational AI solutions in banking, focusing on Connect AI Agents, prompts, and intent/slot tuning.

You will experiment, analyze data, and tune NLU assets to improve conversational quality within IVR frameworks. You will collaborate with the onshore lead, translate technical findings for leadership, and drive delivery with minimal supervision in an established delivery model.

Qualifications

  • 5+ years in data science, ML, NLP or related field.
  • 2+ years building GenAI solutions.
  • Hands-on analytics, experimentation, model evaluation, performance tuning.
  • Experience in conversational AI, NLU, chatbot, IVR use cases.
  • Familiarity with Amazon Connect/Lex or similar platforms.
  • Exposure to LLM/GenAI and modern NLP techniques.

Responsibilities

  • Lead end-to-end delivery of Agentic conversational AI for IVR using Connect/Lex.
  • Run experiments on intent recognition, slot-filling, utterance handling, quality.
  • Analyze interactions, model outputs, test results to identify issues and opportunities.
  • Tune prompts, training data, NLU assets for better performance.
  • Collaborate with onshore lead to refine strategy and priorities.
  • Prepare clear findings and recommendations for leadership.

Skills

GenAI
NLP
Python
Experimentation
Model evaluation
Data analysis
Communication
Delivery orientation
LLM
Tell leadership results

Tools

Amazon Connect
Amazon Lex

Job description

Fractal Analytics Inc. is seeking a hands-on Senior Data Scientist to design and deliver agentic conversational AI solutions in banking, focusing on Connect AI Agents, prompts, and intent/slot tuning.

You will experiment, analyze data, and tune NLU assets to improve conversational quality within IVR frameworks. You will collaborate with the onshore lead, translate technical findings for leadership, and drive delivery with minimal supervision in an established delivery model.

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