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# Sr. Data Scientist

- **Company:** Vgai Solutions Inc
- **Location:** Fort Worth, TX, United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** Microsoft Azure, Business Intelligence Development, Big Data, Software Code Optimization, Continuous Integration, Data Mining, Software Debugging, Monitoring of Systems, Python (Programming Language), Machine Learning, Performance Tuning, Power BI, SQL Databases, Systems Integration, Tableau (Software), Feature Engineering, Apache Spark, Parallel Computation, Modularization, Information Technology, Machine Learning Operations, Code Restructuring, Data Pipelines, Databricks
- **Published:** October 18, 2026
- **Apply:** https://www.dice.com/job-detail/8aa1abeb-38c0-4234-b188-0ea0d73a34d9

## About the Role

* Master's/PhD degree with 3+ years of experience in quantitative discipline (e.g., Data Science, Machine Learning Engineer, Computer Science, Applied Mathematics, Statistics, etc.)
 * Experience with Python programming language
 * Practical experience with data extraction, cleaning, and analysis
 * Depth of knowledge in statistical and machine learning techniques
Preferred qualifications - Education & Prior Job Experience

 * 8+ years of experience in a technical professional environment, in addition to the minimum requirements
 * Experience with SQL and data visualization (Tableau, PowerBI)
 * Practical experience designing, building and deploying machine learning models
 * Experience in using cloud platforms and parallel processing to scale model development/ deployment (Databricks, Azure)
 * 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
Top 3 Must Have Skills:
1.MS or PhD in Data Science, Computer Science, Statistics, or related field
2.Strong Python expertise (production-grade coding, modularization, testing, performance tuning)
3.Hands-on experience with Machine Learning pipeline development and productionization (model deployment, orchestration, monitoring, and optimization)
Nice to Have Skills and Experience:

 1. Experience with Databricks / Spark-based ML pipelines
 2. Proficiency in SQL and working with large-scale datasets
 3. 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:

 1. Has proven experience taking ML models from prototype to production with Python and Databricks.
 2. Demonstrates strong skills in code optimization, debugging, and system integration.
 3. Understands the end-to-end ML lifecycle, including deployment and monitoring.
 4. Is comfortable working with existing codebases and improving them, rather than only building new models.
 5. Clear communication and effective collaboration., Comment: Top 3 Must Haves: 1. MS or PhD in Data Science, Computer Science, Statistics, or related field 2. Strong Python expertise (production-grade coding, modularization, testing, performance tuning) 3. Hands-on experience with Machine Learning pipeline development and productionization (model deployment, orchestration, monitoring, and optimization)

## Description

1. Centralized Machine Learning team supporting 7 business units
 2. Team consists of Senior to Principal-level Data Scientists
 3. Collaborative, supportive, and high-performing culture
 4. Strong focus on quality, innovation, scalability, and measurable revenue impact
How will the resource(s) fit into your team?:

 1. The resource will embed within the centralized ML team and support the Customer Intelligence CBI productionization initiative.
 2. Take ownership of productionizing ML pipelines, including code refactoring and system optimization
 3. Collaborate closely with data scientists, data engineers, and product partners
 4. Accelerate delivery of scalable, production-ready ML solutions