AI Data Scientist – Enterprise AI

Jobtailor; Austin (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor seeks a skilled AI/ML engineer in Austin to design and deploy AI-powered solutions for enterprise problems. You will build data pipelines, evaluate models, and communicate complex concepts to diverse stakeholders.

Join a collaborative, cross-functional team driving predictive analytics, MLOps practices, and scalable AI initiatives across the organization.

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Data Science, ML, AI, Statistics, Engineering, Mathematics, or related field.
• 3+ years of experience developing AI, machine learning, and data science solutions.
• Proficiency in Python and modern AI/ML libraries and frameworks.
• Experience with model evaluation, experimentation, performance measurement, and validation methodologies.
• Experience working with large-scale tabular datasets using SQL, Spark, Databricks, or similar technologies.
• Ability to collaborate effectively in culturally diverse and distributed teams.
• Preferred: 5+ years of industry experience developing AI, machine learning, and data science solutions
• Preferred: Experience with Azure, AWS, or GCP
• Preferred: Version control tools such as GitHub and AI-assisted development tools such as GitHub Copilot
• Preferred: Experience with RAG, prompt engineering, and AI agents
• Preferred: Familiarity with MLOps, model monitoring, observability, and enterprise AI governance
• Preferred: Experience communicating technical concepts to business stakeholders
• Preferred: Experience working in highly collaborative, matrixed organizations

Responsibilities

• Design, develop, and deploy AI-powered solutions using LLMs, Generative AI, machine learning, and predictive analytics
• Develop data pipelines, feature engineering approaches, and analytical workflows
• Research AI methods, tools, and frameworks for enterprise operations business problems
• Design and execute experiments evaluating model effectiveness, accuracy, robustness, and operational performance
• Analyze large-scale structured and semi-structured datasets to generate insights and build predictive models
• Translate business requirements into technical approaches and communicate AI concepts to technical and non-technical audiences
• Support AI solution adoption through training, demonstrations, documentation, and stakeholder engagement
• Collaborate with engineers, data scientists, product owners, business leaders, and technology organizations
• Contribute to AI best practices, reusable frameworks, and technical standards

Skills

AI Solution Development

Machine Learning Expertise

Python Proficiency

Data Pipeline Development

Model Evaluation and Validation

SQL

Spark

Databricks

AI/ML Libraries

Experimentation Methodologies

Education

Bachelor’s, Master’s, or PhD in Computer Science, Data Science, ML, AI, Statistics, Engineering, Mathematics, or related field

Tools

Azure

AWS

GCP

GitHub

GitHub Copilot

Job description

• Design, develop, and deploy AI-powered solutions using LLMs, Generative AI, machine learning, and predictive analytics


• Develop data pipelines, feature engineering approaches, and analytical workflows


• Research AI methods, tools, and frameworks for enterprise operations business problems


• Design and execute experiments evaluating model effectiveness, accuracy, robustness, and operational performance


• Analyze large-scale structured and semi-structured datasets to generate insights and build predictive models


• Translate business requirements into technical approaches and communicate AI concepts to technical and non-technical audiences


• Support AI solution adoption through training, demonstrations, documentation, and stakeholder engagement


• Collaborate with engineers, data scientists, product owners, business leaders, and technology organizations


• Contribute to AI best practices, reusable frameworks, and technical standards

Requirements

• Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Engineering, Mathematics, or a related field


• 3+ years of experience developing AI, machine learning, and data science solutions


• Proficiency in Python and modern AI/ML libraries and frameworks


• Experience with model evaluation, experimentation, performance measurement, and validation methodologies


• Experience working with large-scale tabular datasets using SQL, Spark, Databricks, or similar technologies


• Ability to collaborate effectively in culturally diverse and distributed teams


• Preferred: 5+ years of industry experience developing AI, machine learning, and data science solutions


• Preferred: Experience with Azure, AWS, or GCP


• Preferred: Version control tools such as GitHub and AI-assisted development tools such as GitHub Copilot


• Preferred: Experience with RAG, prompt engineering, and AI agents


• Preferred: Familiarity with MLOps, model monitoring, observability, and enterprise AI governance


• Preferred: Experience communicating technical concepts to business stakeholders


• Preferred: Experience working in highly collaborative, matrixed organizations

Core Competencies

Demonstrates expertise in designing and deploying AI-powered solutions, utilizing machine learning, predictive analytics, and data engineering techniques. Proficient in translating complex technical concepts for diverse audiences and fostering collaboration across teams to drive AI solution adoption.

Highest-signal resume keywords

• AI Solution Development


• Machine Learning Expertise


• Python Proficiency


• Data Pipeline Development


• Model Evaluation and Validation

ATS Optimization Keywords

Hard Skills

• Machine Learning


• Predictive Analytics


• Data Engineering


• Feature Engineering


• Model Evaluation


• SQL


• Spark


• Databricks


• AI/ML Libraries


• Experimentation Methodologies

Soft Skills

• Effective Collaboration


• Communication Skills

Industry Keywords

• Artificial Intelligence


• Data Science


• Enterprise AI Governance


• MLOps


• AI Best Practices

Tools & Technologies

• Azure


• AWS


• GCP


• GitHub


• GitHub Copilot