> Markdown version of [/jobs/ext/3817971-data-scientist-1](https://www.wearedevelopers.com/jobs/ext/3817971-data-scientist-1). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Scientist 1

- **Company:** Epitec, Inc.
- **Location:** Irving, TX, United States
- **Experience:** Experienced
- **Salary:** $106,080.0 - $112,320.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Analysis of Variance (ANOVA), Artificial Neural Networks, Microsoft Azure, Cluster Analysis, Collaborative Software, Information Systems, Data Visualization, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, NumPy, Software Product Management, Microsoft Copilot, SciPy, Workflow Management Systems, Scripting, Google Cloud, Retrieval-Augmented Generation, Large Language Models, Random Forest, Prompt Engineering, Model Validation, Generative AI, Agentic-AI, Pandas, Scikit Learn, Information Technology, Data Analytics, Tools for Reporting, Evaluation of Large Language Models
- **Published:** October 18, 2026
- **Apply:** https://www.dice.com/job-detail/acbafb14-65b6-46ac-a326-85473aa762b3

## About the Role

The ideal candidate has 2+ years of professional experience with Python, machine learning, analytics, and Generative AI and can communicate technical concepts clearly to both technical and non-technical stakeholders., * Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, Business Analytics, or a related quantitative field

 * 2+ years of professional experience in data science, analytics, machine learning, AI, or a related field
 * Hands-on experience with Python, including Pandas, NumPy, SciPy, Scikit-learn, or similar libraries
 * Working knowledge of Generative AI, LLMs, copilots, assistants, agents, prompts, knowledge grounding, and AI-enabled workflows
 * Experience designing, testing, troubleshooting, or evaluating prompts and AI-generated outputs
 * Understanding of machine learning and statistical techniques such as regression, classification, clustering, hypothesis testing, ANOVA, Random Forests, SVMs, or neural networks
 * Experience with data visualization and analytics tools
 * Strong verbal and written communication skills, initiative, patience, problem-solving ability, and teamwork, * Experience with RAG, LangChain/LangGraph, vector databases, prompt engineering, agentic AI, or LLM evaluation
 * Experience with AWS, Azure, Google Cloud, or comparable cloud platforms
 * Understanding of Responsible AI, data privacy, security, governance, and human oversight
 * Experience supporting AI solutions from discovery and experimentation through validation, deployment, adoption, and ongoing support
 * Experience working directly with business users to identify use cases, demonstrate solutions, troubleshoot issues, and encourage adoption
 * Knowledge of APIs, workflow tools, collaboration platforms, scripting, and enterprise data sources

## Description

We are seeking a Data Scientist I to support the adoption and application of Generative AI and agentic technologies across enterprise business teams. This role combines hands-on AI/data science knowledge with business engagement, helping users identify valuable AI use cases, experiment with GenAI tools, troubleshoot solutions, and implement responsible, scalable approaches., * Partner with business stakeholders to identify problems, user needs, and opportunities where Generative AI or agentic capabilities can provide value

 * Configure, test, evaluate, troubleshoot, and document prompts, assistants, agents, AI-enabled workflows, and related user experiences
 * Support prompt design, system instructions, knowledge grounding, structured outputs, agent configuration, and AI response evaluation
 * Translate business requirements into practical GenAI use cases and recommend appropriate tools, approaches, or reusable patterns
 * Troubleshoot issues involving prompts, configurations, AI outputs, data, integrations, and platform behavior
 * Apply Python and data science techniques to data analysis, statistical modeling, machine learning, experimentation, and model validation
 * Collaborate with AI product owners, data scientists, architects, engineering, cybersecurity, governance, privacy, and business teams
 * Explain GenAI capabilities, limitations, risks, responsible usage, and human oversight to business users
 * Document troubleshooting steps, lessons learned, reusable guidance, and best practices