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).