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Entry Level Nvidia Data Scientist Jobs (NOW HIRING)

Bachelor's degree in Data Science, Computer Science, Computer Engineering, Mathematics or related field Level 1: Entry Level Level 2: Minimum 3 years of experience equivalent to a level 1 Level 3: ...

This is an entry level Data Scientist Role for a person who is self motivated and has a passion to innovate and work on cutting edge technology. Qualifications Candidate should have experience in ...

This is an entry level Data Scientist Role for a person who is self motivated and has a passion to innovate and work on cutting edge technology. Qualifications Candidate should have experience in ...

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Junior Data Scientist

Miami, FL ยท On-site

$30 - $35/hr

Job Title: Jr. Data Scientist Location: Miami, FL Employment type ... Fulltime Duration: 2 years Exp: 1-4 years(Entry level) Educational Qualification: Master's Degree ...

Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world's leading technology providers to accelerate the delivery of tomorrow's electronic devices.

Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world's leading technology providers to accelerate the delivery of tomorrow's electronic devices.

Bachelor's degree in Data Science, Computer Science, Computer Engineering, Mathematics or related field Level 1: Entry Level Level 2: Minimum 3 years of experience equivalent to a level 1 Level 3: ...

Associate Data Scientist

Manhattan, NY

$64K - $65K/yr

We are seeking an Associate Data Scientist for this entry-level role. You will work to support the team in building ML-powered analyses and products that shape business strategy, optimize content ...

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Entry Level Nvidia Data Scientist information

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$46K

$165K

$243.5K

How much do entry level nvidia data scientist jobs pay per year?

As of Jul 14, 2026, the average yearly pay for entry level nvidia data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Nvidia Data Scientist vs Entry Level Nvidia Data Analyst?

AspectEntry Level Nvidia Data ScientistEntry Level Nvidia Data Analyst
Required CredentialsBachelor's in Data Science, Computer Science, or related field; knowledge of machine learning and programmingBachelor's in Statistics, Business, or related field; proficiency in data visualization and SQL
Work EnvironmentDeveloping models, analyzing complex data, collaborating with data science teamsData reporting, cleaning, and visualization tasks within business units
Employer & Industry UsageTech companies, AI research, hardware/software developmentBusiness analytics, marketing, finance within Nvidia or partner organizations

Entry Level Nvidia Data Scientist focuses on building predictive models and applying machine learning techniques, while Entry Level Nvidia Data Analyst primarily handles data reporting and visualization. Both roles require strong analytical skills, but data scientists work more on developing algorithms, whereas data analysts focus on interpreting data for business insights.

What are the key skills and qualifications needed to thrive as an Entry Level Nvidia Data Scientist, and why are they important?

To thrive as an Entry Level Nvidia Data Scientist, you need a strong background in statistics, machine learning, and programming (typically Python or C++), usually supported by a relevant degree in computer science, data science, or a related field. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), GPU programming (CUDA), and data visualization tools is highly valued, along with any related certifications. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret data and collaborate across technical and business teams. These skills and qualities are vital for extracting actionable insights from complex data and contributing to innovative AI and computing solutions at Nvidia.

What does an Entry Level Nvidia Data Scientist do?

An Entry Level Nvidia Data Scientist works on analyzing large datasets, developing machine learning models, and leveraging Nvidia's GPU technologies for data processing and AI applications. They collaborate with other engineers and researchers to optimize algorithms for performance on Nvidia hardware. Their responsibilities may include data cleaning, exploratory data analysis, model training, and helping integrate AI solutions into products or services. This role provides opportunities to learn advanced tools and techniques while contributing to cutting-edge projects in AI and deep learning.

What types of projects and data sets can an entry-level Nvidia Data Scientist expect to work on?

As an entry-level Nvidia Data Scientist, you will likely work on projects involving large-scale data analysis, machine learning model development, and AI algorithm optimization. Common tasks include processing GPU-accelerated data, collaborating with engineering teams to test and validate models, and contributing to performance benchmarking. You'll often work with diverse data sets, such as image, video, or sensor data, and participate in cross-functional team meetings. This collaborative environment provides valuable exposure to innovative technologies and offers opportunities to expand your expertise in deep learning and high-performance computing.
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Data Scientist

Data Scientist

Zimmerman Advertising

Fort Lauderdale, FL โ€ข On-site

Full-time

Re-posted 26 days ago


Job description


The Data Scientist works closely with Retail Technology, Media and Account Services teams to provide predictive modeling of Marketing, Direct & Digital Efforts. We are looking for a motivated Data Scientist and analytical thought leader. This is a rare opportunity to be part of a diverse and newly expanded analytics department and a great fit for a predictive modeler with a desire to impact business results.
Responsibilities
  • Apply specialized technical knowledge and expertise to perform reviews relating to the full life cycle of models, information technology applications, or risk management/analysis used across the company.
  • Collaborate and share knowledge with teams across the media organization, as appropriate. Build and maintain relationships with business partners at the manager and staff levels.
  • Use data analysis, mining, and migration techniques for enhanced targeting, audience segmentation, clustering, profiling, and regression analysis
  • Identify digital placement-level strengths and weaknesses across simultaneous campaigns and geographies
  • Develop and maintain internal automated reporting tools, documents, scoring systems, and dashboards for on-going and post-campaign reporting
  • Coordinate cross-functional reviews to discuss region- and campaign-specific findings and actionable recommendations for digital media campaigns built on various CPM, CPC, CPE, and CPA models
  • Identify and facilitate resolution of tagging issues in coordination with Traffic and Production teams focused on site-side tracking, reporting, and implementation
  • Provide client-facing/non-technical recommendations and insights, both in a written and verbal manner, that provide understandable and actionable optimizations.
  • Work with Media, Strategic Intelligence and Account Services teams to develop measurement plans to deliver on campaign and client objectives

Requirements
  • Bachelor's degree in related field
  • Entry-Level and/or College Internship experience
  • Must demonstrate the ability to successfully develop and run analytics (scripts) using specialized tools and platforms, specifically, R, Python, SQL, and/or SAS.
  • Experience applying data synthesis, mining and regression techniques for enhanced targeting, audience segmentation, clustering, profiling, and insightful recommendations
  • Advanced knowledge of Microsoft Excel
  • General understanding of digital advertising, digital media strategy, ad placement type, placement-level insight, and standard media metrics is preferred
  • Experience with data orchestration tools such as Annalect Omni is preferred
  • Excellent verbal, written and interpersonal communication skills
  • Ability to work independently and as part of a team
  • Ability to manage multiple projects simultaneously while meeting deadlines
  • Regression modeling focusing on maximizing yield while measuring the diminishing returns of ad spend at scale for thousands of locations.
  • Data storytelling and presentation