Mastech Digital
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist in Irving, TX, on a W2 contract. Requires 2+ years in statistical data science, Python, SQL, and ML model deployment in AWS/Azure. Familiarity with Docker and marketing data ecosystems preferred.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
January 9, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Irving, TX
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🧠 - Skills detailed
#Mathematics #A/B Testing #AI (Artificial Intelligence) #Computer Science #Customer Segmentation #Databricks #Data Science #Spark (Apache Spark) #AWS (Amazon Web Services) #Deployment #PySpark #SQL (Structured Query Language) #Python #Data Management #Azure #ML (Machine Learning) #Kubernetes #Docker #DMP (Data Management Platform)
Role description
Contract Type: W2 Only
Job Title: Data Scientist
Location: Irving, TX
We are seeking a mid-level Data Scientist to join our team and help drive personalized customer experiences through customer segmentation and online experimentation. In this role, you will build and deploy machine learning models, design and analyze A/B tests, and translate business objectives into data-driven insights that directly influence marketing and product decisions.
This role is ideal for someone who enjoys combining statistical rigor, applied machine learning, and business impact in a fast-paced, collaborative environment.
Required Skills:
• Research, prototype, and develop AI/ML solutions for customer segmentation and personalization.
• Design, execute, and analyze online controlled experiments (A/B tests, multivariate tests) to validate hypotheses and measure business impact.
• Build, deploy, monitor, and analyze machine learning models in production environments.
• Apply statistical experimentation techniques when launching and iterating on AI-driven products.
• Partner closely with data, product, marketing, and engineering teams to align solutions with business goals.
• Translate complex analytical findings into clear, actionable insights for non-technical stakeholders.
• Stay current with emerging tools, frameworks, and best practices in data science and experimentation.
• Deliver high-quality work on time with a strong focus on research rigor, innovation, and engineering excellence.
• Demonstrate measurable impact through data science applied to marketing and personalization use cases.
Basic Qualifications:
• 2+ years of experience in statistical data science, feature engineering, and customer segmentation.
• 2+ years of hands-on experience with Python, SQL, and PySpark.
• 2+ years of experience training, evaluating, and deploying machine learning models.
• 2+ years of experience productionizing ML workloads in AWS or Azure.
• Familiarity with containerized deployments using Docker and/or Kubernetes.
• Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, or equivalent practical experience.
Preferred Qualifications:
• Experience working with the Databricks platform.
• Experience building ML models using large-scale structured and unstructured data.
• Exposure to MarTech ecosystems, such as: Customer Data Platforms (CDPs); Data Management Platforms (DMPs); Email Service Providers (ESPs)
• Experience integrating data science solutions into marketing and personalization workflows.
Contract Type: W2 Only
Job Title: Data Scientist
Location: Irving, TX
We are seeking a mid-level Data Scientist to join our team and help drive personalized customer experiences through customer segmentation and online experimentation. In this role, you will build and deploy machine learning models, design and analyze A/B tests, and translate business objectives into data-driven insights that directly influence marketing and product decisions.
This role is ideal for someone who enjoys combining statistical rigor, applied machine learning, and business impact in a fast-paced, collaborative environment.
Required Skills:
• Research, prototype, and develop AI/ML solutions for customer segmentation and personalization.
• Design, execute, and analyze online controlled experiments (A/B tests, multivariate tests) to validate hypotheses and measure business impact.
• Build, deploy, monitor, and analyze machine learning models in production environments.
• Apply statistical experimentation techniques when launching and iterating on AI-driven products.
• Partner closely with data, product, marketing, and engineering teams to align solutions with business goals.
• Translate complex analytical findings into clear, actionable insights for non-technical stakeholders.
• Stay current with emerging tools, frameworks, and best practices in data science and experimentation.
• Deliver high-quality work on time with a strong focus on research rigor, innovation, and engineering excellence.
• Demonstrate measurable impact through data science applied to marketing and personalization use cases.
Basic Qualifications:
• 2+ years of experience in statistical data science, feature engineering, and customer segmentation.
• 2+ years of hands-on experience with Python, SQL, and PySpark.
• 2+ years of experience training, evaluating, and deploying machine learning models.
• 2+ years of experience productionizing ML workloads in AWS or Azure.
• Familiarity with containerized deployments using Docker and/or Kubernetes.
• Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, or equivalent practical experience.
Preferred Qualifications:
• Experience working with the Databricks platform.
• Experience building ML models using large-scale structured and unstructured data.
• Exposure to MarTech ecosystems, such as: Customer Data Platforms (CDPs); Data Management Platforms (DMPs); Email Service Providers (ESPs)
• Experience integrating data science solutions into marketing and personalization workflows.
