Lead Data Scientist with AI and Cloud

EPAM Systems; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

EPAM Systems is seeking a Lead Data Scientist to architect AI-driven data platforms and scalable data applications.

The role collaborates with software engineers, ML engineers, data engineers, and business stakeholders to deliver production-ready AI solutions across cloud and hybrid environments.

Qualifications

• Experience delivering AI or data solutions into production.
• Strong Python skills and front-end basics (React/JS/TS).
• SQL proficiency for relational and analytical databases.
• REST APIs, Git and modern software engineering standards.
• Knowledge of data warehousing and ETL/ELT concepts.
• Power BI data modeling and reporting.
• English at B2 level or above.

Responsibilities

• Build AI Agents using modern LLM frameworks for analytics and automation.
• Connect AI Agents to internal data sources, APIs and enterprise systems.
• Help build the internal platform to host, deploy and monitor AI Agents with reusable modules.
• Create data apps and interfaces using Python and React/JavaScript with APIs and dashboards.
• Develop analytical models and Power BI outputs with standards for consistency.
• Develop and maintain ETL/ELT pipelines for reliable data delivery.
• Implement AI solutions across cloud and hybrid environments.
• Maintain CI/CD pipelines for AI agents and data apps.
• Engage stakeholders to gather requirements and drive adoption.

Skills

Python

SQL

REST APIs

CI/CD

Data modeling

Tools

React

JavaScript

TypeScript

Git

Power BI

Job description

A top oil and gas company is looking for a motivated and talented Lead Data Scientist with expertise in AI and Cloud technologies. In this role, you will collaborate with Software Engineers, Machine Learning Engineers, Data Engineers, and business stakeholders to understand requirements and convert them into scalable, dependable AI-driven solutions. Your work will include building AI Agents, full-scale data applications, and the internal platform supporting them, as well as the data pipelines, cloud infrastructure, and automation processes behind them.

Responsibilities

Build AI Agents using modern LLM frameworks to support analytics assistance, automation, and decision-making, covering prompt engineering, tool integration, memory handling, and orchestration logic for dependable agent performance Connect AI Agents to internal data sources, APIs, and enterprise systems Help build the internal platform used to host, deploy, and monitor AI Agents, while creating reusable modules for orchestration, evaluation, observability, and governance Create complete data applications, tools, and interfaces using Python and React/JavaScript, including APIs, dashboards, and interactive tools that deliver advanced analytics to business users Build advanced analytical models and Power BI outputs, while establishing standards and templates that promote consistency and reusability Develop and maintain ETL/ELT pipelines that process and deliver reliable data for AI and analytics purposes Implement and manage AI solutions across cloud and hybrid environments, leveraging managed AI, compute, and storage resources effectively Assist in maintaining CI/CD pipelines for AI agents and data applications Engage with internal stakeholders and business teams to collect requirements, gather feedback, and encourage adoption of AI solutions.

Requirements

At least 5 years of experience in related positions (AI Engineer, ML Engineer, Data Engineer), with practical experience delivering AI or data solutions into production Strong proficiency in Python Advanced skills in React, JavaScript, and TypeScript for front-end development Capability to write efficient SQL queries for relational and analytical databases Hands-on experience developing and consuming REST APIs, using Git, and applying modern software engineering standards Solid grasp of data architecture principles, including data warehousing, data lakes, and ETL/ELT processes Practical experience with Power BI, covering data modeling and report creation English language skills at a B2 level or above

Nice to have

Knowledge of LLM and agent frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or AutoGen Exposure to vector database technologies