Sr Data Scientist

Location: Fort Worth, TX 76155 (Hybrid)
Duration: 6-12+ Months with possible extension and conversion to full-time

About the Role

We are seeking a Data Scientist to support the Service Recovery Modernization initiative. This resource will be embedded within the project team and will take ownership of the end-to-end development of machine learning and Generative AI solutions.

Responsibilities

• Work closely with the Service Recovery Modernization team to understand business needs and identify AI and machine learning opportunities.
• Collect, clean, transform, and prepare structured and unstructured data for analysis and modeling.
• Design, build, and maintain reliable data pipelines for ML and Generative AI applications.
• Develop, train, test, and validate machine learning models.
• Design and develop Generative AI applications using large language models.
• Deploy ML and GenAI solutions into production environments.
• Monitor model performance, accuracy, reliability, and data quality.
• Troubleshoot data, pipeline, and model-related issues.
• Collaborate with data engineers, software engineers, product owners, and business stakeholders.
• Document data processes, model designs, testing results, and deployment procedures.
• Follow security, privacy, governance, and responsible AI standards.

Requirements

• Experience working as a Data Scientist, Machine Learning Engineer, or in a similar role.
• Strong experience with data preparation, cleansing, transformation, and feature engineering.
• Hands-on experience designing and developing data pipelines.
• Strong programming skills in Python and SQL.
• Experience developing, testing, and deploying machine learning models.
• Experience building Generative AI or large language model applications.
• Understanding of the complete ML lifecycle, including development, validation, deployment, and monitoring.
• Experience working with structured and unstructured datasets.

Preferred Qualifications

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch.
• Knowledge of LLM orchestration, prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation.
• Experience with MLOps tools, CI/CD pipelines, model monitoring, and containerized deployment.
• Experience delivering AI solutions for customer service, operational recovery, or process modernization initiatives.
• Familiarity with data governance, model governance, and responsible AI practices.

Pay

$90 - $100 per hour

Benefits

• Medical, dental, and vision insurance
• 401K contributions
• Paid time off (PTO)
• Sick leave
• Other benefits mandated by applicable state or localities