Data Scientist

Propertyvalue Prudent Technologies And Consulting
Fort Worth, TX, United States
25 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Health Informatics Continuous Integration Python (Programming Language) Machine Learning Performance Tuning Tensorflow Unstructured Data Pytorch Large Language Models Deep Learning Model Validation
+4 more
Scikit Learn Kubernetes Machine Learning Operations Data Pipelines

Requirements

  • 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.

Preferred Skills:

  • Health sciences domain experience - clinical research, healthcare analytics, life sciences, or pharma ML applications
  • Experience with NVIDIA RAPIDS for accelerated data science workflows.
  • Experience with NVIDIA NeMo or Triton Inference Server for model development and deployment.
  • Experience with generative AI / LLM fine-tuning and deployment on NVIDIA infrastructure.
  • NVIDIA Deep Learning Institute (DLI) or Dell AI technology certifications.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.dice.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:35 min

Preventing remote code execution in PyTorch models

Balázs Kiss · WWC 2023

1:39 min

Fundamentals of tensors and the TensorFlow library

Håkan Silfvernagel · LIVE

2:28 min

Understanding Kubernetes architecture and core cluster components

Marc Nimmerrichter · WWC 2022

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

1:06 min

Compiling PyTorch environments for advanced time forecasting

Christoph Lohrmann Christoph Lohrmann +1 · WWC Europe 2026

3:14 min

Structuring career paths and localized data architectures

Ulrich Wurstbauer +1 · LIVE

Videos

See all

Related articles

See all