Senior Data Scientist

• Job Title: Senior Data Scientist
• Client & Practice Area: Prudent Data & AI Practice
• Experience Required: 7+ years of professional data science / applied ML experience
• Employment Type: Full-time/Direct Hire (No C2C)
• Location: Hybrid in the DFW area; project will being as onsite T, W, Th in Fort Worth, TX (Candidates must be local)

Role Summary:

Prudent Consulting is seeking a Senior Data Scientist to design, train, and deploy machine learning models on Dell AI Factory (Dell + NVIDIA) infrastructure. Working closely with data engineering, this role will leverage the centralized data warehouse to build production-grade ML solutions that drive measurable business outcomes. The ideal candidate brings deep applied ML expertise combined with hands-on experience in GPU-accelerated model development and deployment.

Key Responsibilities:

• Design, build, and validate machine learning and statistical models to address key TCU business problems.
• Train and optimize models at scale using GPU-accelerated infrastructure (Dell AI Factory, NVIDIA AI Enterprise stack), including deep learning workloads.
• Partner with data engineering to define data requirements, feature engineering pipelines, and ML-ready datasets from the centralized data warehouse.
• Deploy models into production using MLOps best practices, including versioning, monitoring, and retraining pipelines.
• Evaluate model performance, bias, and drift, ensuring responsible and explainable AI practices.
• Translate business problems into analytical frameworks and communicate findings to technical and non-technical stakeholders.
• Stay current on emerging ML/AI techniques and NVIDIA AI tooling to bring innovative solutions to the client.
• Mentor junior data scientists and contribute to reusable modeling frameworks and best practices.

Required Skills & Experience:

• 7+ years of hands-on experience in data science, applied machine learning, or advanced analytics roles.
• Strong proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
• Direct, hands-on experience building and deploying models on Dell AI Factory / NVIDIA AI Enterprise GPU-accelerated infrastructure — required.
• Strong foundation in statistics, machine learning algorithms, and model evaluation techniques.
• Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, model registries, CI/CD for ML).
• Experience working with large-scale structured and unstructured datasets sourced from enterprise data warehouses.
• Strong stakeholder communication skills, with the ability to translate complex analysis into business impact.

Education Requirements:

Master's or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field (or equivalent practical experience).