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Senior Nvidia Data Scientist Jobs (NOW HIRING)

We are an Elite and Premier partner to Google Cloud, AWS, NVIDIA, Snowflake, and other leading ... Senior Data Scientist (AWS) Experience Level: 8+ years Employment type: Full Time Location: Remote ...

NVIDIA is at the forefront of the AI revolution, and our research is shaping the future of large ... for a Senior Scientist to join our team and help advance our capabilities in synthetic data ...

NVIDIA is at the forefront of the AI revolution, and our research is shaping the future of large ... Senior Scientist to join our team and help advance our capabilities in generating synthetic data ...

IntelliGenesis is seeking a Senior Data Scientist to support IG Labs working to answer challenging ... Experience NVIDIA Technology & frameworks * Experience with data transport and transformation APIs ...

We are looking for a Product Marketing Manager to join the NVIDIA Data center product marketing ... Undergraduate education or equivalent experience in computer science, computer engineering, or a ...

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Senior Nvidia Data Scientist information

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$41.5K

$142.5K

$201K

How much do senior nvidia data scientist jobs pay per year?

As of Aug 3, 2026, the average yearly pay for senior nvidia data scientist in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 per year, depending on experience, location, and employer.

What is the difference between Senior Nvidia Data Scientist vs Nvidia Data Scientist?

AspectSenior Nvidia Data ScientistNvidia Data Scientist
Required CredentialsMaster's or PhD in Data Science, Computer Science, or related field; extensive experienceBachelor's or Master's in relevant field; some experience preferred
Work EnvironmentAdvanced research teams, project leadership roles, cross-functional collaborationData analysis, model development, support tasks within teams
Employer & Industry UsageTech companies, AI research labs, GPU hardware firmsSimilar industries, entry to mid-level roles in AI and data analytics

The main difference between a Senior Nvidia Data Scientist and a Nvidia Data Scientist lies in experience, responsibilities, and leadership. Senior roles typically involve project leadership, advanced research, and strategic input, while Nvidia Data Scientists focus on data analysis and model development. Both roles require strong technical skills and familiarity with Nvidia's technologies, but senior positions demand more experience and a broader scope of responsibilities.

What cities are hiring for Senior Nvidia Data Scientist jobs? Cities with the most Senior Nvidia Data Scientist job openings:
What are the most commonly searched types of Nvidia Data Scientist jobs? The most popular types of Nvidia Data Scientist jobs are:
What states have the most Senior Nvidia Data Scientist jobs? States with the most job openings for Senior Nvidia Data Scientist jobs include:
Infographic showing various Senior Nvidia Data Scientist job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 10% Part Time, and 9% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.

Senior Data Scientist_ Hybrid (Full-time)

Prudent Technologies and Consulting

Fort Worth, TX • On-site

Other

Posted 15 days ago


Job description

Senior Data Scientist_ Onsite

Full-time/Direct Hire

Fort Worth, Texas

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.

Preferred / Added Value Skills:

  • Health sciences domain experience clinical research, healthcare analytics, life sciences, or pharma ML applications (e.g., predictive diagnostics, patient outcome modeling, regulatory-compliant AI).
  • 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.

Education Requirements:

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