Chief Data Scientist

EPAM Systems, Inc.; Comisión de Fomento de Perú; Híbrido; ARS 226.487.000 - 317.082.000; Jornada completa

Descripción de la vacante

EPAM Systems, Inc. is seeking a Chief Data Scientist with deep expertise in Large Language Models (LLMs) and Python to shape AI-powered chatbot solutions for specialized use cases.

You will influence product, analytics, and engineering to craft a sophisticated shopping assistant chatbot and push the boundaries of prompt engineering. Lead cross-functional teams, design robust evaluation methods, and develop LLM-based agents that securely interface with APIs, databases, and external tools via

Formación

• Minimum 7 years of applied data science experience.
• At least 2 years in people management with 10+ FTEs overseen.
• Strong practical experience with LLMs and OpenAI APIs on Azure.
• Proficient Python for AI workflow integration and fine-tuning.
• Hands-on background creating AI agents using function calling.
• Knowledge of hallucination mitigation and responsible AI practices.
• Experience in NLP and Conversational AI development.
• English at B2 level or higher with strong written and spoken skills.

Responsabilidades

• Partner with product, analytics, and engineering to shape a shopping assistant chatbot.
• Design and refine prompt engineering strategies to improve interactions.
• Create LLM-based agents linking with APIs, databases and tools via function calling.
• Maintain chatbot reliability and mitigate hallucinations through evaluation techniques.
• Apply A/B testing frameworks to enhance chatbot performance over time.
• Embed Responsible AI and regulatory alignment in all activities.
• Guide data and cloud engineering on infrastructure for AI-powered chatbots.
• Lead exploratory data analysis to surface insights for data engineering.

Conocimientos

LLMs

Python

OpenAI API (Azure)

Team leadership

Chatbot development

NLP

Responsible AI

MLOps

Herramientas

Azure

APIs

Databases

Descripción del empleo

We are searching for a Chief Data Scientistwith deep expertise in Large Language Models (LLMs) and Python to shape AI-powered chatbot solutions for specialized use cases.

Responsibilities

• Partner with cross-functional groups across product, analytics, and engineering to develop and refine a shopping assistant chatbot
• Design and improve prompt engineering strategies to raise the quality of chatbot interactions
• Create LLM-based agents that link with APIs, databases, and external tools via function calling
• Preserve chatbot reliability and mitigate hallucinations by employing model evaluation techniques
• Leverage A/B testing frameworks to assess and progressively enhance chatbot performance
• Put Responsible AI and compliance principles into practice to ensure ethical and regulatory alignment
• Run exploratory data analysis to surface insights and draft structured requirements for the data engineering team
• Guide cloud engineering teams on the infrastructure needs supporting AI-powered chatbot solutions

Requirements

• A minimum of 7 years of applied professional experience in data science
• No less than 2 years of experience in people management or team leadership, overseeing a team of 10 or more FTEs
• Advanced expertise in LLMs, including practical work with OpenAI APIs on Azure
• Strong Python skills for integrating and fine-tuning AI workflows
• Hands-on background in building AI agents that leverage function calling to interact with external tools and databases
• Working knowledge of hallucination prevention techniques for maintaining chatbot accuracy and reliability
• Sound understanding of Responsible AI and compliance best practices, including ethical AI guidelines
• Experience in Natural Language Processing (NLP) and Conversational AI development
• English at B2 level or higher, with strong written and spoken communication abilities

Nice to have

• Practical background in A/B testing and experimentation, working closely with analytics teams
• Capability to design and implement a testing strategy driven by key performance metrics for chatbots
• Confident use of exploratory data analysis (EDA) to draw insights from data
• Skill in defining and conveying data requirements to the data engineering team
• Familiarity with cloud services, either through hands-on experience or the ability to outline requirements for cloud engineering teams