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Temporary Nvidia Data Scientist Jobs in Indiana (NOW HIRING)

Through our unparalleled science, data, technology and laboratory network, we advance diagnostics ... Employees regularly scheduled to work less than 20 hours, Casual, Intern, and Temporary employees ...

Through our unparalleled science, data, technology and laboratory network, we advance diagnostics ... Employees regularly scheduled to work less than 20 hours, Casual, Intern, and Temporary employees ...

Performs QC review of data. * Informs Study Director, Principal Investigator and/or management of ... Employees regularly scheduled to work less than 20 hours, Casual, Intern, and Temporary employees ...

Performs QC review of data. * Informs Study Director, Principal Investigator and/or management of ... Employees regularly scheduled to work less than 20 hours, Casual, Intern, and Temporary employees ...

Physical AI Senior Manager

Indianapolis, IN ยท 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 ...

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Temporary Nvidia Data Scientist information

What is the difference between Temporary Nvidia Data Scientist vs Temporary Nvidia Data Analyst?

AspectTemporary Nvidia Data ScientistTemporary Nvidia Data Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related field; experience with machine learning and AIBachelor's in Data Analysis, Statistics, or related; proficiency in data visualization and SQL
Work EnvironmentCollaborates with AI/ML teams on complex models, often in R&D settingsSupports business insights, reports, and dashboards within corporate or project teams
Employer & Industry UsageTech companies, AI research labs, GPU-focused firmsBusiness intelligence, finance, marketing, and data-driven industries

Temporary Nvidia Data Scientists focus on developing AI and machine learning models, requiring advanced technical skills and research experience. In contrast, Temporary Nvidia Data Analysts primarily interpret data, create reports, and support decision-making with less emphasis on AI/ML techniques. Both roles are essential in tech and data-driven industries but serve different functions within organizations.

What are the most commonly searched types of Nvidia Data Scientist jobs in Indiana? The most popular types of Nvidia Data Scientist jobs in Indiana are:
What cities in Indiana are hiring for Temporary Nvidia Data Scientist jobs? Cities in Indiana with the most Temporary Nvidia Data Scientist job openings:
Scientific Data Architect- Central US

Scientific Data Architect- Central US

TetraScience

Indianapolis, IN โ€ข On-site

$61 - $78.50/hr

Full-time

PTO

Posted 8 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 worldโ€™s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScienceโ€™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 โ€œThe Tetra Way,โ€ 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 customersโ€™ 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 candidateโ€™s specific experience, localized market data, and internal team equity.