Job Title
Principal Data Scientist
Location & Work Model
Dallas, TX / Long Term Contract
About the Role
We are seeking a high-performing Machine Learning professional to embed within our centralized ML team and drive the productionization initiative for Customer Intelligence (CBI). In this role, you will take ownership of transitioning ML models from prototype to production, refactoring code, and optimizing systems. You will collaborate closely with Senior and Principal Data Scientists, Data Engineers, and Product Partners to deliver scalable, high-impact ML solutions across 7 business units.
· Position Type: Contract
· Interview Process: 3-4 rounds (Initial virtual interviews followed by in-person rounds)
Team Environment & Structure
· Structure: Centralized Machine Learning team supporting 7 core business units.
· Composition: Senior to Principal-level Data Scientists.
· Culture: Collaborative, supportive, and high-performing with a focus on quality, innovation, scalability, and measurable revenue impact.
Key Responsibilities
· Embed within the centralized ML team to lead the productionization, deployment, and optimization of ML pipelines for the CBI initiative.
· Refactor existing code bases, optimize system performance, and improve code modularization, testing, and debugging.
· Manage the end-to-end ML lifecycle, including model orchestration, deployment, monitoring, and performance tuning.
· Work with existing codebases to enhance maintainability and scalability rather than solely building new models from scratch.
· Partner with cross-functional teams including Data Scientists, Data Engineers, and Product leads to accelerate production-ready deliverables.
Key Requirements
Top Must-Have Qualifications
1. Education: Master’s or PhD degree in a quantitative discipline (Data Science, Computer Science, Statistics, Applied Mathematics, Machine Learning Engineering, etc.) with 3+ years of experience.
2. Python Expertise: Production-grade coding skills, including modularization, unit testing, performance tuning, and debugging.
3. ML Pipeline Productionization: Hands-on experience developing, deploying, orchestrating, monitoring, and optimizing end-to-end machine learning pipelines in production.
Minimum Qualifications
· 3+ years of relevant experience in a quantitative discipline.
· Practical experience with data extraction, cleaning, and analysis.
· Solid theoretical and applied knowledge of statistical and machine learning techniques.
Preferred Qualifications & Skills
· 8+ years of technical experience in a professional environment.
· Hands-on experience taking ML models from prototype to production using Databricks and Spark-based ML pipelines.
· Proficiency in SQL and working with large-scale datasets.
· Experience with cloud platforms (Azure) and parallel processing to scale model deployment.
· Familiarity with ML lifecycle tools (MLflow, CI/CD, model monitoring framework).
· Prior consulting experience or domain knowledge in the airline industry.
· Familiarity with data visualization tools (Tableau, PowerBI).
Ideal Candidate Profile
· Technical Rigor: Proven track record of taking prototypes to production in Python and Databricks with strong feature engineering capabilities.
· Systems Mindset: Strong competency in code optimization, debugging, and system integration. Comfortable diving into existing codebases to optimize and scale them.
· Collaborative Communicator: Ability to communicate clearly across technical and non-technical stakeholders at all organizational levels while working seamlessly on a diverse team.
About VGAI Solutions
VGAI Solutions is an AI-native and technology solutions firm that helps organizations build high-performing engineering and technology teams. MBE-certified and ISO 9001-registered, we operate across the USA, Mexico, UAE, Mauritius, and India, with our Global Delivery Center in Hyderabad. From specialized IT to engineering talent to end-to-end AI solutions, we deliver the human capital that powers our Fortune 1000 clients.
Equal Opportunity Statement
VGAI Solutions is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, disability, veteran status, or any other protected characteristic.
