Fort Worth, TX, United StatesPosted Aug 21, 2026OnsiteOpen
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About this opportunity
Sr. Data Scientist Work Model: Hybrid – Onsite Tuesday–Thursday; Remote Monday & Friday Interview: 3–4 rounds – Screening, 1–2 Technical/Coding rounds, Final In-Person $60/hr Education: Master’s or PhD in Data Science, Computer…
Sr. Data Scientist
Location: Fort Worth, TX
Work Model: Hybrid – Onsite Tuesday–Thursday; Remote Monday & Friday
Interview: 3–4 rounds – Screening, 1–2 Technical/Coding rounds, Final In-Person
$60/hr
Education: Master’s or PhD in Data Science, Computer Science, Statistics, Mathematics, ML, or related quantitative field
Technical assessment must demonstrate hands-on skills in
Python
Generative AI
SQL
Job Description
We are looking for a hands-on Senior Data Scientist with strong experience in Python, Generative AI, Machine Learning, and production AI/ML pipelines.
The engineer will support the Service Recovery Modernization initiative within the ML/AI team supporting Contact Centers and Digital Customer Experience. The role requires someone who can take AI/ML solutions from prototype through production, including data preparation, model development, deployment, orchestration, monitoring, and optimization.
The ideal candidate should have practical experience building Gen AI applications using LLMs, RAG, prompt engineering, classifiers, knowledge bases, and Agentic AI, along with strong production-grade Python development skills.
Key Responsibilities
Design, develop, test, and deploy Machine Learning and Generative AI applications.
Build customer-facing Gen AI solutions using LLMs, RAG, prompt engineering, classifiers, knowledge bases, and AI evaluation techniques.
Develop and optimize ML/AI pipelines from data preparation through production deployment.
Deploy, orchestrate, monitor, and optimize machine learning models in production.
Develop production-quality Python code with proper modularization, testing, debugging, and performance tuning.
Work with Azure ML and Databricks to build and productionize AI/ML solutions.
Apply statistical and machine learning techniques to solve complex business problems.
Perform feature engineering and analyze data from multiple perspectives to improve model performance.
Implement appropriate AI guardrails, privacy, security, and cybersecurity considerations.
Work with existing codebases, improve existing solutions, and develop new applications from the ground up.
Collaborate with data scientists, data engineers, product teams, and other technical stakeholders.
Contribute to scalable, reliable, and measurable AI solutions that deliver business and revenue impact.
Required Skills
5–7 years of Data Science / Machine Learning experience
Master's or PhD in a quantitative/technical discipline
Strong Python programming skills
Hands-on experience building Generative AI applications
Strong knowledge of LLMs and Agentic AI
Experience with RAG, prompt engineering, classifiers, knowledge bases, and LLM evaluation
Hands-on experience building ML/AI pipelines
Experience with model deployment, orchestration, monitoring, and optimization
Strong understanding of statistical and machine learning techniques
Experience taking ML/AI solutions from prototype to production
Strong debugging, code optimization, and system integration skills
Nice-to-Have Skills
Azure ML
Databricks
SQL
MLflow
CI/CD for ML
Model monitoring
Microsoft Dynamics
Airline industry experience
Consulting experience
Experience with production-grade containerized ML applications
Ideal Candidate
The ideal candidate is not just a research-focused Data Scientist. They should be a hands-on engineer who can build Gen AI applications and take ML models all the way into production.
Strong candidates will have demonstrated experience with Python + LLMs/Agentic AI + RAG + ML pipelines + Azure ML, along with the ability to handle deployment, monitoring, optimization, security, and integration challenges.
Team & Project
The resource will be embedded within the ML/AI team supporting Contact Centers and Digital Customer Experience and will contribute to the Service Recovery Modernization initiative.
Responsibilities will include ownership of
Data preparation
Data pipelines
ML/Gen AI application design
Model development
Testing
Deployment
Production monitoring and optimization
The team is collaborative and high-performing, with a strong focus on quality, innovation, scalability, and measurable business impact.
Interested in this position?
Review your details and resume before submitting your application.