Temporary Data Scientist Machine Learning Jobs in Texas

Job Summary

• Seeking a Data Scientist with a strong focus on Machine Learning to drive the development and deployment of models that directly impact customer experience and business performance.
• This role is responsible for building, optimizing, and scaling models that support core platform functionality such as search, ranking, and predictive analytics.
• The position plays a critical role in transforming large scale data into actionable insights and intelligent systems that improve decision making and operational efficiency.
• This role is best suited for a candidate with 5 or more years of experience who is both technically strong and business minded.
• Success requires the ability to identify high value opportunities, execute independently, and deliver measurable outcomes.
• Collaborate closely with engineering and cross functional teams to ensure models are production ready and aligned with business goals.
• Design, develop, and optimize machine learning models for search, ranking, and recommendation systems
• Build classification models to predict user behavior such as cancellations and engagement patterns
• Develop predictive models to support pricing and revenue optimization strategies
• Analyze large datasets to identify trends, patterns, and opportunities for improvement
• Perform feature engineering to enhance model performance and accuracy
• Partner with engineering teams to deploy models into production environments
• Ensure models are scalable, reliable, and maintain consistent performance over time
• Design and execute A B testing frameworks to evaluate model effectiveness
• Build dashboards and reports to communicate insights and performance metrics
• Translate complex technical findings into clear, actionable insights for stakeholders
• Continuously research and implement new machine learning techniques to improve outcomes
• Machine Learning is core to their role (70-90%), not just a small portion
• Can build, deploy, and own models in production within a small team environment.

• 5 or more years of experience in Data Science or Machine Learning Engineering
• Strong proficiency in Python and machine learning libraries
• Solid understanding of statistical modeling, experimentation, and data analysis
• Experience owning the full model lifecycle including data preparation, modeling, deployment, and monitoring
• Strong SQL skills with experience working on large datasets
• Experience working in cloud environments such as GCP or similar platforms
• Strong communication skills with the ability to explain technical concepts clearly
• Experience with MLOps tools and best practices is preferred
• Industry experience in marketplace, travel, or financial services is a plus
• 5-10+ years in Data Science or Machine Learning roles
• Currently or recently owning ML models for one company (not consulting or multiple clients)
• Experience owning the full lifecycle of machine learning models, from data preparation and feature engineering through deployment and performance monitoring.
• Hands on experience across the full lifecycle:
  
  • Data extraction and cleaning
  • Feature engineering
  • Model development and tuning
  • Production deployment
  • Monitoring and iteration
• Experience building models tied to:
  
  • Search or ranking
  • Recommendations
  • Pricing or forecasting
  • User behavior prediction (conversion, churn, cancellations)
• Experience deploying models into production (not just offline work)
• Strong understanding of experimentation and A B testing
• In house Data Scientist at a consumer product, marketplace, travel, or ecommerce company
• Experience improving conversion, revenue, or engagement through ML models
• Exposure to MLOps practices and working closely with engineering teams
• Comfortable as a senior individual contributor with full ownership
• Experience in fast paced or startup environments
• Strong business judgment, understands tradeoffs not just modeling

• Competitive benefits package including health coverage
• Flexible work environment
• Opportunity to work on high impact, data driven initiatives
• Career growth in a fast paced, technology focused environment