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Chief Data Scientist

Reads like an AI Engineer role: building products on existing AI models.

Pay
Pay not listed
Work setting
Remote — work setting source
Work setup in the employer’s posting: TELECOMMUTE
From the employer’s posting
Employment
Not stated

What you’ll work on

Full posting
  • Craft and enhance a shopping assistant chatbot with product, analytics and engineering teams

  • Develop LLM-based agents that call APIs, databases and third-party services

  • Design and iterate on prompt engineering to improve chatbot dialogue quality

  • Evaluate models to keep chatbot outputs stable and reduce hallucinations

  • Run A/B tests to measure and grow chatbot effectiveness

From the employer’s posting
Collaborate with cross-disciplinary teams across product, analytics, and engineering to craft and enhance a shopping assistant chatbot
Develop LLM-based agents that connect with APIs, databases, and third-party services through function calling
Design and iterate on prompt engineering techniques to lift the quality of chatbot dialogues
Ensure chatbot stability and minimize hallucinations by employing thorough model evaluation practices
Apply A/B testing frameworks to gauge and steadily boost chatbot effectiveness

Tools in this posting

  • Python
  • Azure
Source — Tool mentions in context
We are seeking a Chief Data Scientist with extensive expertise in Large Language Models (LLMs) and Python to develop AI-powered chatbot solutions for specialized use cases. The ideal candidate offers a strong grounding in Natural Language Processing (NLP) and Conversational AI, together with practical experience in hallucination reduction, Responsible AI and compliance, and data analysis. Responsibilities Collaborate with cross-disciplinary teams across product, analytics, and engineering to craft and enhance a shopping assistant chatbot Design and iterate on prompt engineering techniques to lift the quality of chatbot dialogues Develop LLM-based agents that connect with APIs, databases, and third-party services through function calling Ensure chatbot stability and minimize hallucinations by employing thorough model evaluation practices Apply A/B testing frameworks to gauge and steadily boost chatbot effectiveness Integrate Responsible AI and compliance foundations to secure ethical behavior and regulatory alignment Conduct exploratory data analysis (EDA) to reveal insights and translate them into precise specifications for the data engineering team Guide cloud engineering teams on the infrastructure prerequisites needed for AI-driven chatbot rollouts Requirements At least 7 years of applied professional experience in data science or AI-focused roles A minimum of 2 years of leadership and team management background Strong mastery of Large Language Models, including working experience with OpenAI APIs on Azure Advanced Python development skills for connecting, orchestrating, and enhancing AI workflows Proven history of creating AI agents that leverage function calling to interact with external systems and databases Sound understanding of hallucination mitigation techniques to keep chatbot outputs accurate and reliable Clear grasp of Responsible AI and compliance principles, together with ethical AI guidelines Established expertise in Natural Language Processing (NLP) and Conversational AI development Strong English communication abilities at B2 level or higher, in both written and spoken formats Nice to have Hands-on experience with A/B testing and experimentation, partnering closely with analytics teams Ability to shape and put in place a testing framework built around key performance metrics tailored to chatbot solutions Command of exploratory data analysis (EDA) to extract meaningful patterns from large datasets Capability to prepare clear, structured data requirements for the data engineering team Awareness of cloud services, whether through direct hands-on involvement or by defining infrastructure needs for cloud engineering teams

Posting record

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Actively hiringFirst seen by us 12 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 1, 202612 days ago
Recorded sightings
14
Last seen by us
Nov 14, 2026
Employer says posted
Oct 9, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 12

Similar jobs usually come down between day 4 and day 77.

From 51 similar postings that came down. Coming down is not always a hire.

EPAM Systems is hiring

673 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

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About EPAM Systems

People
About 3,012 in 2024.Benefit plan filings (Form 5500)
Company
Listed as EPAM.
H-1B visas
21 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for AI Engineer roles

New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.

Weekly new AI Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 7, the most 65, and the latest week had 65.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under AI Engineer, by the work the posting describes.

AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.

Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.

An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.

Job description

View original posting ↗

We are seeking a Chief Data Scientist with extensive expertise in Large Language Models (LLMs) and Python to develop AI-powered chatbot solutions for specialized use cases. The ideal candidate offers a strong grounding in Natural Language Processing (NLP) and Conversational AI, together with practical experience in hallucination reduction, Responsible AI and compliance, and data analysis. Responsibilities Collaborate with cross-disciplinary teams across product, analytics, and engineering to craft and enhance a shopping assistant chatbot Design and iterate on prompt engineering techniques to lift the quality of chatbot dialogues Develop LLM-based agents that connect with APIs, databases, and third-party services through function calling Ensure chatbot stability and minimize hallucinations by employing thorough model evaluation practices Apply A/B testing frameworks to gauge and steadily boost chatbot effectiveness Integrate Responsible AI and compliance foundations to secure ethical behavior and regulatory alignment Conduct exploratory data analysis (EDA) to reveal insights and translate them into precise specifications for the data engineering team Guide cloud engineering teams on the infrastructure prerequisites needed for AI-driven chatbot rollouts Requirements At least 7 years of applied professional experience in data science or AI-focused roles A minimum of 2 years of leadership and team management background Strong mastery of Large Language Models, including working experience with OpenAI APIs on Azure Advanced Python development skills for connecting, orchestrating, and enhancing AI workflows Proven history of creating AI agents that leverage function calling to interact with external systems and databases Sound understanding of hallucination mitigation techniques to keep chatbot outputs accurate and reliable Clear grasp of Responsible AI and compliance principles, together with ethical AI guidelines Established expertise in Natural Language Processing (NLP) and Conversational AI development Strong English communication abilities at B2 level or higher, in both written and spoken formats Nice to have Hands-on experience with A/B testing and experimentation, partnering closely with analytics teams Ability to shape and put in place a testing framework built around key performance metrics tailored to chatbot solutions Command of exploratory data analysis (EDA) to extract meaningful patterns from large datasets Capability to prepare clear, structured data requirements for the data engineering team Awareness of cloud services, whether through direct hands-on involvement or by defining infrastructure needs for cloud engineering teams
Source details

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