Minimum Qualifications – Education & Prior Job Experience: Master or PhD degree with 5+ years of experience in quantitative discipline (e.g., Data Science, Machine Learning Engineer, Computer Science, Applied Mathematics, Statistics, etc.). Hands on experience with building Gen AI applications – prompt engineering, classifiers, knowledge bases, RAG solutions, LLMs as judges, etc.
Numbers & Facts
Location
Fort Worth, TX
Description
Title: Sr Data Scientist
Location: Fort Worth, TX - 76155
Duration: 12+ months contract
Work mode: 3 days hybrid onsite (Tue/Wed/Thu)
Top 3 Mandatory Skills and Experience:
Proficient in Python
Experience/knowledge on designing and implementing Gen AI applications
Hands-on experience with Machine Learning and AI pipeline build, model deployment, orchestration, monitoring, and optimization
Master or PhD degree with 5+ years of experience in quantitative discipline (e.g., Data Science, Machine Learning Engineer, Computer Science, Applied Mathematics, Statistics, etc.)
Experience with ML lifecycle tools (e.g., MLflow, CI/CD, model monitoring)
Practical experience designing, building and deploying machine learning models
Domain knowledge in the airline industry
Experience working in a consulting role
Skills, Licenses & Certifications:
Ability to effectively communicate both verbally and written with all levels within the organization
Demonstrated motivation and aptitude for logical analysis, problem identification, and problem solving
Ability to view data from different angles to employ feature engineering techniques to better represent models
Ability to work on a diverse team with diverse skillsets
5-7 years of experience required
Nice to Have Skills:
Client Dynamics
Prompt Engineering
Proficiency in SQL and working with data
Experience with ML lifecycle tools (e.g., MLflow, CI/CD, model monitoring)
Describe a great candidate that you are looking for and what skills and experience they will have:
Has experience with LLMs and Agentic AI
Has experience building customer facing Gen AI applications; awareness on guardrails, privacy, cybersecurity concerns
Has proven experience taking ML models from prototype to production with Python and Azure ML; containerize where needed.
Demonstrated strong skills in code optimization, debugging, and system integration.
Understands end-to-end ML lifecycle, including deployment and monitoring.
Is comfortable working with existing codebases and improving them, as well as building new ones from scratch. Clear communication and effective collaboration.
What is the team environment and structure like?:
ML/AI team supporting Contact Centers and Digital Customer Experience
Will collaborate with several team members
Collaborative, supportive, and high-performing culture
Strong focus on quality, innovation, scalability, and measurable revenue impact
How will the resource fit into your team?:
The resource will be embedded within the team and support the Service Recovery Modernization initiative.
Take ownership of data preparation, data pipelines, design, test, and deployment of ML and Gen AI applications.
Collaborate closely with data scientists, data engineers, and product partners.
Accelerate delivery of scalable, production-ready AI solutions.