Fort Worth, TX (Hybrid) Contract
Education & Prior Job Experience
• 14+ years of experience in a technical professional environment, in addition to the minimum requirements
• Strong understanding and hands on -building traditional ML model (classification, Regression and all varities of Supervised Models)
* Strong hands on Deep Learning Algorithm and implementations
* Advance AIML knowledge
* Must have deployed the end to end Machine Learning pipeline.
• Practical experience designing, building and deploying machine learning models
-Experience with SQL and data visualization (Tableau, PowerBI)
•Platform mindset + reuse — building shared components/templates/patterns used by multiple teams (not one off implementations).
•Operational readiness for AI — monitoring/telemetry, production maintenance practices, and reliability-focused troubleshooting.
• AI Platform architecture, API design, distributed systems, reliability engineering- building reusable platform components used by multiple teams (not one off apps)
• Experience implementing AI quality/evaluation practices and AI telemetry/monitoring foundations.
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 work on a diverse team with diverse skillsets
Top 4 Must Have Skills: (with MS/Phd)
Python, Machine Learning, Deep Learning , ML design and deployment
Nice to Have Skills: Databricks, Azure ML, SQL, Tableau/PowerBI
Describe a great candidate that you are looking for and what skills and experience they will have:
Experienced data scientist with ML/DL model training, deployment, and evaluation. Advanced in Python and Databricks. Good communication and collaboration. Consulting background is a plus.
What is the team environment and structure like?:
Centralized ML team supporting 7 business units. All team members are data scientist levels from senior to principal level. Team culture is friendly, supportive, and collaborative. Focus on quality, innovation, and revenue impact.
How will the resource(s) fit into your team?:
The resource will embed within the centralized ML team and support active Loyalty and Marketplace projects. They will independently execute model development, validation, and deployment tasks while collaborating with peer data scientists, data engineers, and product partners.
Thanks & Regards
Mohammad Faisal
