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.
Lead 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 postingBuild LLM-driven agents that call APIs, databases and external services
Shape and fine-tune prompt engineering to improve chatbot conversations
Evaluate models rigorously to reduce hallucinations and protect reliability
Run A/B tests to assess and raise chatbot performance
Run exploratory data analysis and turn insights into data engineering requirements
From the employer’s posting
Build LLM-driven agents that interface with APIs, databases, and external services via function calling
Shape and fine-tune prompt engineering approaches to raise the quality of chatbot conversations
Protect chatbot dependability and reduce hallucinations by applying rigorous model evaluation methods
Use A/B testing frameworks to assess and progressively elevate chatbot performance
Carry out exploratory data analysis (EDA) to surface insights and convert them into well-defined requirements for the data engineering team
Tools in this posting
- Python
- Azure
Source — Tool mentions in context
We are looking for a Lead Data Scientist with deep knowledge of Large Language Models (LLMs) and Python to create AI-driven chatbot solutions for targeted use cases. The ideal candidate brings a solid foundation in Natural Language Processing (NLP) and Conversational AI, along with hands-on experience in hallucination mitigation, Responsible AI and compliance, and data analytics. Responsibilities Team up with multidisciplinary groups spanning product, analytics, and engineering to design and improve a shopping assistant chatbot Shape and fine-tune prompt engineering approaches to raise the quality of chatbot conversations Build LLM-driven agents that interface with APIs, databases, and external services via function calling Protect chatbot dependability and reduce hallucinations by applying rigorous model evaluation methods Use A/B testing frameworks to assess and progressively elevate chatbot performance Embed Responsible AI and compliance principles to ensure ethical operation and regulatory conformity Carry out exploratory data analysis (EDA) to surface insights and convert them into well-defined requirements for the data engineering team Advise cloud engineering teams on the infrastructure requirements essential to AI-powered chatbot deployments Requirements No less than 5 years of hands-on professional experience in data science or applied AI positions At least 1 year of experience guiding and managing development teams Strong command of Large Language Models, including practical work with OpenAI APIs on Azure Advanced Python programming abilities for integrating, orchestrating, and refining AI workflows Track record of building AI agents that use function calling to engage with external tools and databases Solid grasp of hallucination prevention methods to preserve chatbot precision and dependability Firm understanding of Responsible AI and compliance best practices, along with ethical AI standards Demonstrated experience in Natural Language Processing (NLP) and Conversational AI creation Confident English communication skills at B2 level or above, in both writing and speech Nice to have Practical background in A/B testing and experimentation, working closely alongside analytics teams Skill in defining and executing a testing strategy grounded in key performance indicators specific to chatbot solutions Proficiency in exploratory data analysis (EDA) for drawing valuable insights from sizable datasets Aptitude for producing clear, structured data specifications for the data engineering team Familiarity with cloud services, whether through direct hands-on work or by outlining infrastructure requirements for cloud engineering teams
Posting record
Report an errorActively 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
EPAM Systems is hiring
673 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordYour next step
Check the employer’s posting for the current role and application details.
Already applied? Track this application
Has EPAM Systems posted this job before?
Yes. We’ve followed 4 other Lead Data Scientist jobs there since November 2026. All 4 are still up.
Large employers often post one title for several teams, so these can be separate openings.
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.
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
We are looking for a Lead Data Scientist with deep knowledge of Large Language Models (LLMs) and Python to create AI-driven chatbot solutions for targeted use cases. The ideal candidate brings a solid foundation in Natural Language Processing (NLP) and Conversational AI, along with hands-on experience in hallucination mitigation, Responsible AI and compliance, and data analytics. Responsibilities Team up with multidisciplinary groups spanning product, analytics, and engineering to design and improve a shopping assistant chatbot Shape and fine-tune prompt engineering approaches to raise the quality of chatbot conversations Build LLM-driven agents that interface with APIs, databases, and external services via function calling Protect chatbot dependability and reduce hallucinations by applying rigorous model evaluation methods Use A/B testing frameworks to assess and progressively elevate chatbot performance Embed Responsible AI and compliance principles to ensure ethical operation and regulatory conformity Carry out exploratory data analysis (EDA) to surface insights and convert them into well-defined requirements for the data engineering team Advise cloud engineering teams on the infrastructure requirements essential to AI-powered chatbot deployments Requirements No less than 5 years of hands-on professional experience in data science or applied AI positions At least 1 year of experience guiding and managing development teams Strong command of Large Language Models, including practical work with OpenAI APIs on Azure Advanced Python programming abilities for integrating, orchestrating, and refining AI workflows Track record of building AI agents that use function calling to engage with external tools and databases Solid grasp of hallucination prevention methods to preserve chatbot precision and dependability Firm understanding of Responsible AI and compliance best practices, along with ethical AI standards Demonstrated experience in Natural Language Processing (NLP) and Conversational AI creation Confident English communication skills at B2 level or above, in both writing and speech Nice to have Practical background in A/B testing and experimentation, working closely alongside analytics teams Skill in defining and executing a testing strategy grounded in key performance indicators specific to chatbot solutions Proficiency in exploratory data analysis (EDA) for drawing valuable insights from sizable datasets Aptitude for producing clear, structured data specifications for the data engineering team Familiarity with cloud services, whether through direct hands-on work or by outlining infrastructure requirements for cloud engineering teams
Source details
Source notes
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- Pay
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- Location & working pattern
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- Work authorization
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