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Nvidia Data Scientist Jobs in Indiana (NOW HIRING)

Scientific Data Architect- Central US

Chicago, IL · On-site

$65.75 - $84.50/hr

About TetraScience TetraScience is the Scientific Data and AI Company building Tetra OS, the ... TetraScience's growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher ...

Physical AI Senior Manager

Indianapolis, IN · On-site

$120K - $159K/yr

... NVIDIA, Siemens, AWS and others). Candidates should be comfortable in factories, warehouses, and ... Lead and mentor multi-disciplinary teams: data science, ML engineering, software and edge, vision ...

... Functions, API Gateway, Data Science, Autonomous Database, and Oracle Integration Cloud ... Experience with LangChain, LangGraph, NVIDIA NIM, or Hugging Face * Experience leading AI or ERP ...

Nvidia Data Scientist information

See Indiana salary details

$43.8K

$157K

$231.7K

How much do nvidia data scientist jobs pay per year?

As of Jul 26, 2026, the average yearly pay for nvidia data scientist in Indiana is $157,025.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,000.00 and $161,800.00 per year, depending on experience, location, and employer.

What is the salary of a data scientist in NVIDIA?

The average salary for a data scientist at NVIDIA typically ranges from $100,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized expertise in AI and machine learning may earn higher compensation, often including bonuses and stock options.

Is a data scientist job still in demand?

Data scientist jobs remain in high demand across various industries due to the increasing reliance on data-driven decision making. Skills in machine learning, statistical analysis, and programming languages like Python or R are highly valued, and the role often offers competitive salaries and growth opportunities.

What is a Nvidia Data Scientist job?

A Nvidia Data Scientist leverages AI, machine learning, and deep learning to develop models and algorithms that optimize GPU-accelerated computing solutions. They work with large datasets, conduct research, and build scalable data-driven solutions for industries like gaming, autonomous vehicles, and healthcare. Their role involves collaborating with engineers and researchers to improve AI frameworks and performance on Nvidia hardware. Proficiency in Python, deep learning frameworks (TensorFlow, PyTorch), and data analytics is essential.

What are the key skills and qualifications needed to thrive in the Nvidia Data Scientist position, and why are they important?

To thrive as an Nvidia Data Scientist, you need a solid background in statistics, machine learning, computer science, and typically a graduate degree in a related field. Proficiency with Python, deep learning frameworks (such as TensorFlow or PyTorch), GPU computing, and experience with large-scale data systems are highly valued, along with relevant certifications. Analytical thinking, strong problem-solving abilities, and clear communication are soft skills that set candidates apart in this collaborative, fast-evolving field. These capabilities are essential for driving innovation, building robust AI solutions, and contributing effectively to cross-functional teams at Nvidia.

What are the entry-level jobs at NVIDIA?

Entry-level jobs at NVIDIA for data scientists typically include roles such as Data Analyst, Junior Data Scientist, or Data Science Intern. These positions often require foundational skills in programming, statistics, and machine learning, and may involve working with NVIDIA's AI and GPU technologies. Internships and co-op programs are common pathways for recent graduates to enter the company as entry-level data scientists.

What types of projects do Nvidia Data Scientists typically work on, and how do they contribute to the company's core technologies?

Nvidia Data Scientists are often involved in pioneering projects related to AI model development, computer vision, natural language processing, and deep learning applications optimized for GPU hardware. They collaborate closely with research engineers, software developers, and product teams to create scalable AI solutions that enhance Nvidia’s products, ranging from gaming to autonomous systems. A typical week might involve experimenting with new algorithms, analyzing large datasets, optimizing code for GPU acceleration, and translating research breakthroughs into practical applications. This role offers continuous learning opportunities and plays a direct part in shaping industry-leading technologies.

How difficult is it to get hired at NVIDIA?

Getting hired as a data scientist at NVIDIA can be competitive, requiring strong technical skills in machine learning, deep learning, and programming languages like Python or C++. Candidates often need relevant experience, a solid educational background, and a good understanding of NVIDIA's technologies and products. The hiring process typically involves multiple interviews and technical assessments.
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Infographic showing various Nvidia Data Scientist job openings in Indiana as of July 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Hybrid job distribution, with an average salary of $157,025 per year, or $75.5 per hour.
Scientific Data Architect- Central US

Scientific Data Architect- Central US

TetraScience

Indianapolis, IN • On-site

$61 - $78.50/hr

Full-time

PTO

Posted 6 days ago


Job description

About TetraScience

TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft.

In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you.

Who You Are

You are a product-minded, outcome-obsessed driver of technical scientific solutions.

You a high velocity self-starter. You refuse to let uncertainty obstruct your path to designing and building solutions.

You roll up your sleeves, try things out, and get things done. You do not hesitate to prototype, demo, and build in order to accelerate delivery of products for your end users.

You thrive in environments where you can collaborate with scientists, product managers, and engineers to transform complex scientific data into actionable outcomes. Your ability to engage with scientists and business leaders alike makes you a key player in maximizing the value of scientific data.

With rich experience applying cutting edge data methodologies to the biopharma R&D domain, you bridge understanding between present-day pain points and generalizable solutions.

You are an insatiable learner, with a track record of deeply learning new tools, methods, and domains.

You fundamentally embody the principles of extreme ownership and have a demonstrated history of building extensible data models and applications for Biopharma end users to maximize value from their data via analysis and integration with AI/ML.

This role will require extreme self-discipline and determination as we forge a category that will fundamentally and forever change the life science industry.

What You Have Done
  • PhD with +4 years or Masters with +8 years of industry experience in life sciences with extensive domain knowledge in drug discovery (target ID through lead optimization), preclinical development, CMC (all drug modalities), or product quality testing.
  • Proven track record of defining, designing, prototyping, and implementing productized AI/ML-driven use cases in cloud environments
  • Collaborated with cross-functional teams, including product managers, software engineers, and scientific stakeholders.
  • Performed extensive exploratory data analysis and workflow optimization to enable scientific outcomes not previously possible.
  • Engaged diverse audiences, from scientists to executive stakeholders using your excellent communication and storytelling abilities.
  • Advised scientists in a consulting capacity to further research, development, and quality testing outcomes.

Requirements

What You Will Do
  • You will be a critical team member in a unique partnership to industrialize Scientific AI. As such, you will engage directly with customers onsite a couple of days per week in the Indianapolis area, building strong relationships, deeply understanding their scientific data challenges and requirements, and accelerating solutions.
  • Design and implement extensible, reusable data models that efficiently capture and organize scientific data for scientific use cases, ensuring scalability and future adaptability.
  • Translate scientific data workflows into robust solutions leveraging the Tetra Data Platform.
  • Own, scope, prototype, and implement solutions including:
    • Data model design (tabular & JSON)
    • Python-based parser development.
    • Lab software (e.g., ELN/LIMS) integration via APIs.
    • Data visualization and app development in Python (using app frameworks like Streamlit and plotting tools like holoviews and Plotly)
    • Collaborate with Scientific Business Analysts (SBAs), customer scientists and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid)
    • Programmatically interrogating proprietary instrument output files.
  • Dynamically iterate with scientific end users and technical stakeholders to rapidly drive solution development and adoption through regular demos and meetings
  • Proactively communicate implementation progress and deliver demos to customer stakeholders.
  • Collaborate with the product team to build and prioritize our roadmap by understanding customers’ pain points within and outside Tetra Data Platform.
  • Rapidly learn new technologies (e.g., new AWS services or scientific analysis applications) to develop and troubleshoot use cases
  • Must be able to travel to client sites in St.Louis, Indianapolis, Chicago regions.

Benefits

  • Competitive Salary and equity in a fast-growing company.
  • Supportive, team-oriented culture of continuous improvement.
  • Generous paid time off (PTO).
  • Flexible working arrangements - Remote work when not at Customer Sites

We are not currently providing visa sponsorship for this position.

The salary range for this position is $140,000 - $240,000. The salary range posted reflects our target baseline for this role. Final compensation is determined by a thorough evaluation of factors including the candidate’s specific experience, localized market data, and internal team equity.