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Entry Level Bachelor Applied Science Jobs (NOW HIRING)

Grid

Applied Scientist

Seattle, WA · On-site

$120K - $200K/yr

... a bachelors or master's degree in Statistics, Mathematics, Physics, or Computer Science with a ... Proven experience in applied machine learning, including a deep understanding of statistical ...

Grid

Applied Scientist

Seattle, WA · On-site

$120K - $200K/yr

... a bachelors or master's degree in Statistics, Mathematics, Physics, or Computer Science with a ... Proven experience in applied machine learning, including a deep understanding of statistical ...

Clipboard Health

Applied Scientist

San Francisco, CA · On-site

$160K - $225K/yr

About the Role We're building a new team, Applied Science, and we're looking for our first outside ... Bachelor's degree in quantitative field: economics, statistics, engineering, mathematics, etc or ...

The Trade Desk

Applied Scientist II

Irvine, CA

... science, graph mining, and machine learning. * Unlock your product-focused mindset. With your ... You have a Bachelor's/Master's/PhD level degree in a quantitative discipline. Not everyone has the ...

Shannon Health

Diagnostic Tech

San Angelo, TX · On-site

Education Education Type Program of Study Required/Preferred High School Diploma N/A Required Associate degree Applied Science or Related Field Required Bachelor's degree Applied Science or Related ...

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All JobsEntry Level Bachelor Applied Science Jobs

Entry Level Bachelor Applied Science information

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$29.5K

$100.3K

$241.5K

How much do entry level bachelor applied science jobs pay per year?

As of Jun 9, 2026, the average yearly pay for entry level bachelor applied science in the United States is $100,265.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,500.00 and $106,000.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Bachelor Applied Science vs Entry Level Bachelor Science?

AspectEntry Level Bachelor Applied ScienceEntry Level Bachelor Science
CredentialsBachelor's degree in Applied Science or related fieldBachelor's degree in Science (e.g., Biology, Chemistry)
Work EnvironmentPractical settings, labs, industry sitesResearch labs, academic institutions, offices
Employer & Industry UsageManufacturing, healthcare, technology companiesResearch institutions, universities, government agencies
Common Search & ComparisonYesYes

Entry Level Bachelor Applied Science typically focuses on practical, industry-oriented skills, preparing graduates for technical roles in various industries. Entry Level Bachelor Science emphasizes theoretical knowledge and research skills, often leading to roles in academia or research. Both degrees are valuable but serve different career paths based on practical versus theoretical focus.

More about Entry Level Bachelor Applied Science jobs
What cities are hiring for Entry Level Bachelor Applied Science jobs? Cities with the most Entry Level Bachelor Applied Science job openings:
What are the most commonly searched types of Bachelor Applied Science jobs? The most popular types of Bachelor Applied Science jobs are:
What states have the most Entry Level Bachelor Applied Science jobs? States with the most job openings for Entry Level Bachelor Applied Science jobs include:
What job categories do people searching Entry Level Bachelor Applied Science jobs look for? The top searched job categories for Entry Level Bachelor Applied Science jobs are:
Entry Level Bachelor Applied Science jobs near you
Infographic showing various Entry Level Bachelor Applied Science job openings in the United States as of May 2026, with employment types broken down into 2% As Needed, 80% Full Time, 5% Part Time, 12% Contract, and 1% Nights. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $100,265 per year, or $48.2 per hour.
Applied Scientist

Applied Scientist

Grid

Seattle, WA • On-site

$120K - $200K/yr

Full-time

Posted 19 days ago

Job description

About us
Today’s financial system is built to favor those with money. Grid’s mission is to level that playing field by building financial products that help users better manage their financial future. The Grid app lets users access cash, build credit, spend money, optimize their taxes, and lots, lots more.

Grid is a fast-growing team that’s deeply passionate about making a difference in the lives of millions. We’re solving huge problems and believe that every team member has a big role to play. Come join our growing team in our brand new Seattle office!

The role
We’re adding an Applied Scientist to our team to help us build and scale our core product lines. You'll work closely with product, engineering and business leaders to make a difference with data. With access to multiple robust datasets and clear research objectives, you'll have a significant impact on Grid's progress as a business—as well as our users' happiness and success.

Projects will include fraud detection, prevention and mitigation in novel arenas, such as risk underwriting for various lending/advance programs; predictive analytics to drive our payout and repayments systems; and more.
 
The team
We're focused on serving our users and building a robust product and business above all else. To this end, Grid's team members experience high levels autonomy and ownership, and as a company we value curiosity, learning and growth.

As an Applied Scientist, you'll have an opportunity not only to identify key leverage points for our data products, but also to set the standard for Grid's statistical inference and machine learning practice.

The tech stack
Our backend tech stack is based on Python, GCP, Go, protobufs, BigQuery and MySQL. We have built our platform from the ground up to optimize for clean data sources, and we have made numerous investments into data warehousing, streaming analytics infrastructure and offline data cleanliness. As a result, we think Grid is positioned for efficient and powerful applied science.
What you'll do
  • Research & Analysis: Perform data research and analysis using Grid's proprietary dataset as well as other relevant sources
  • Model Development: Develop and validate models that enable strategically relevant business objectives, such as enabling growth, mitigating fraud, controlling risk, etc.
  • Deployment & Iteration: Iterate on new and existing models based on feedback from team and real-world performance
  • Productionization: Collaborate with data engineers, product managers to help translate your work into production-grade, high scaled data products
  • Present Findings: Present your findings and communicate with members of the team with varying levels of technical depth
  • Foster DS @ Grid: Help build out our Applied Science and Machine Learning as a team and practice at Grid
What we're looking for:
  • Applied Science Expertise: Proven experience in Machine Learning and/or Applied Science, including a strong background in statistical inference, machine learning. This is a requirement, a bachelors or master's degree in Statistics, Mathematics, Physics, or Computer Science with a focus on machine learning is required. We are currently not accepting applicants with bachelor or master's degrees in Business Analytics, Information Systems, or Data Science.
  • Deep Expertise in Applied Science & Machine Learning: Proven experience in applied machine learning, including a deep understanding of statistical inference and predictive modeling. Demonstrated practical experience with deep learning techniques, particularly transformer-based models.
  • Research to Implementation Proficiency: A strong track record of reading, understanding, and implementing research papers in machine learning or related fields.
  • Robust Technical Skills: Hands-on experience with Python (with libraries like PyTorch/TensorFlow) and SQL is essential.
  • Autonomy and Initiative: Ability to work independently and take ownership of projects, showcasing a proactive approach to identifying key leverage points for data products.
  • Curiosity and Optimism: People who are constantly asking why the world around them works the way it does, and who have the will to change it.
  • Technical Skills: Proficiency in the modern machine learning techniques, such as Model Evaluation and Validation, Deep Learning and Time Series Analysis, Logistic Regression, Naive Bayes, Tree based Models (i.e., Random Forest).
  • Self Starter: Confidence to prioritize work and delivery demonstrable results on a tight cadence.
  • Domain Knowledge: Demonstrated experience or understanding of the financial industry, especially in the context of building and scaling FinTech products.
Benefits
Medical
Dental
Vision
401K
Life Insurance

Salary Range
$120,000 - $200,000 per year

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.