Sr. Data Scientist - Conversational AI

Acunor; United States; A distancia; USD 150.000 - 200.000; Jornada completa

Descripción de la vacante

Acunor Inc. is seeking a hands-on Senior Data Scientist to design, develop and improve agentic conversational AI solutions within a banking-like environment. The role focuses on Amazon Connect, Amazon Lex, agentic prompts, and NLU/tuning for IVR applications.

You will analyze interaction data, run experiments and refine NLP assets to raise conversational quality, delivering with leadership and business stakeholders while driving delivery priorities in a fast-paced setting.

Formación

• 5+ years of data science, ML, NLP or related field.
• Experience building GenAI solutions.
• Strong analytics, experimentation and model evaluation skills.
• Experience delivering conversational AI, NLU, chatbots or IVR.

Responsabilidades

• Support end-to-end conversational AI capabilities for IVR built on Amazon Connect/Lex.
• Design, run, and interpret experiments on intent recognition and prompt handling.
• Analyze data, model outputs and test results to identify issues and improvements.
• Tune intents, training data, prompts and related NLU assets.
• Collaborate with leads to refine slot-filling approaches and delivery priorities.
• Evaluate LLM/GenAI capabilities supporting NLU and understanding.
• Present findings and performance results to leadership and stakeholders.
• Identify risks and help manage project timelines.

Conocimientos

Data science

Machine learning

NLP

GenAI

NLU

Amazon Connect

Amazon Lex

Python

Experimentation

Model evaluation

IVR use cases

Conversation AI

Descripción del empleo

Senior Data Scientist - Conversational AI

Location: United States - Remote

Employment Type: Full-Time

Role Overview

We are seeking a hands-on Senior Data Scientist to design, develop and improve agentic conversational AI solutions within a banking environment. The role focuses on Amazon Connect, Amazon Lex, agentic prompts, and intent and slot tuning for IVR applications.

You will analyze interaction data, run experiments and refine NLU assets to improve conversational quality. This delivery-focused position requires strong analytical skills, the ability to contribute quickly, and clear communication with technical leads and business stakeholders.

Key Responsibilities

• Support end-to-end delivery of conversational AI capabilities for IVR solutions built on Amazon Connect and Amazon Lex.
• Design, execute and interpret experiments involving intent recognition, slot filling, utterance handling and conversational quality.
• Analyze interaction data, model outputs and test results to identify issues and improvement opportunities.
• Tune intent descriptions, training data, prompts and related NLU assets.
• Collaborate with the onshore lead to refine slot-filling approaches, conversation behavior and delivery priorities.
• Evaluate and implement LLM and GenAI capabilities supporting NLU and intent understanding.
• Present findings, recommendations and performance results to leadership and project stakeholders.
• Identify delivery risks, resolve issues and support project timelines.

Required Qualifications

• 5+ years of experience in data science, machine learning, NLP or a related field.
• 2+ years of experience building GenAI solutions.
• Strong hands-on experience with analytics, experimentation, model evaluation and performance tuning.
• Experience delivering conversational AI, NLU, chatbot, virtual assistant or IVR use cases.
• Strong familiarity with Amazon Connect and Amazon Lex, or highly comparable experience with similar conversational AI platforms.
• Experience applying LLM, GenAI or modern NLP techniques to intent understanding and conversational AI.
• Ability to ramp up quickly and contribute within an established delivery environment.
• Strong written and verbal communication skills, including presenting technical findings to leadership and partner teams.

Preferred Qualifications

• Production experience tuning intent classification, slot filling, fallback handling or dialogue behavior.
• Strong Python and data analysis skills for experimentation, reporting and model evaluation.
• Experience with prompt-based evaluation or LLM-assisted NLU workflows.
• Experience collaborating across onshore and offshore delivery teams.