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Full Time Linear Algebra Jobs (NOW HIRING)

Intrepid Studios

Gameplay Programmer

San Diego, CA

$136K - $151K/yr

Understanding of linear algebra is a solid bonus Additional Information The gaming industry can be ... All posted positions are on-site, full-time, with generous medical benefits options, paid sick ...

Intrepid Studios

Gameplay Programmer

San Diego, CA · On-site

$136K - $151K/yr

Understanding of linear algebra is a solid bonus Additional Information The gaming industry can be ... All posted positions are on-site, full-time, with generous medical benefits options, paid sick ...

Embedding VC

AI Research Engineer

Mountain View, CA · On-site

$241K/yr

This is a full-time, in-person position based in Mountain View, CA. Responsibilities * Participate ... Strong foundation in algorithms, linear algebra, statistics, and machine learning principles.

OceanComm, Inc.

Engineering Intern / Co-op

Chicago, IL · On-site

$35 - $55/hr

Many of our past interns have gone on to join OceanComm full-time. Strong performers will be ... Comfort with linear algebra * Experience with web development (especially TypeScript / Vue)

OceanComm, Inc.

Engineering Intern / Co-op

Chicago, IL · On-site

$35 - $55/hr

Many of our past interns have gone on to join OceanComm full-time. Strong performers will be ... Comfort with linear algebra * Experience with web development (especially TypeScript / Vue)

Chipton Ross

Software Engineer

Camden, NJ · On-site

$75/hr

Strong mathematics background in linear algebra, statistical analysis and signal processing ... HOURS * Full-Time- 4/10-1st Shift. ADDITIONAL * Active Secret or higher Clearance. ADDITIONAL ...

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How much do full time linear algebra jobs pay per hour?

As of Jul 22, 2026, the average hourly pay for full time linear algebra in the United States is $28.85, according to ZipRecruiter salary data. Most workers in this role earn between $27.40 and $30.29 per hour, depending on experience, location, and employer.

What is the difference between Full Time Linear Algebra vs Data Analyst?

AspectFull Time Linear AlgebraData Analyst
Required CredentialsBachelor's or higher in Mathematics, Linear Algebra, or related fieldsBachelor's in Statistics, Mathematics, or related fields; often requires data analysis certifications
Work EnvironmentResearch labs, academic institutions, or technical departmentsBusiness offices, tech companies, or consulting firms
Industry UsageAcademic research, education, or specialized technical rolesBusiness intelligence, marketing, finance, and operations
Common Search/ComparisonFull Time Linear Algebra vs Data Analyst

While Full Time Linear Algebra focuses on theoretical and applied mathematical concepts, Data Analysts utilize these skills to interpret data and support decision-making in various industries. Both roles often require strong analytical skills and familiarity with data tools, but their primary applications and work environments differ.

What are the key skills and qualifications needed to thrive as a Linear Algebra Instructor, and why are they important?

To thrive as a Linear Algebra Instructor, you need a solid background in mathematics, typically with at least a master's degree in math or a related field, and experience in teaching or tutoring. Familiarity with educational technology tools such as learning management systems (LMS), digital whiteboards, and software like MATLAB or Python (NumPy) is often required. Strong communication, patience, and the ability to explain complex concepts clearly are essential soft skills. These qualifications ensure effective instruction, student engagement, and successful learning outcomes in both in-person and online educational environments.

What are Full Time Linear Algebra jobs?

Full Time Linear Algebra jobs are positions that require a strong understanding of linear algebra concepts and techniques, typically applied in areas such as data science, engineering, research, and finance. These roles often involve working with matrices, vectors, and algorithms to solve complex problems, analyze data, or develop mathematical models. Common job titles include data scientist, machine learning engineer, quantitative analyst, and research scientist. Working full-time in such roles usually means a standard 40-hour work week with benefits and opportunities for career advancement. Employers often look for candidates with a background in mathematics, computer science, or engineering.

What are some common challenges faced by professionals working full-time in linear algebra roles, and how can they be addressed?

Professionals in full-time linear algebra roles often encounter challenges such as translating complex theoretical concepts into practical applications, especially when working with large datasets or real-time systems. Collaborating with interdisciplinary teams, such as software engineers or data scientists, can require clear communication to bridge knowledge gaps. Staying updated with the latest computational tools and algorithms is also essential. These challenges can be addressed by participating in ongoing professional development, actively seeking feedback from colleagues, and leveraging open-source resources or collaborative platforms to enhance both technical and teamwork skills.
More about Full Time Linear Algebra jobs
What cities are hiring for Full Time Linear Algebra jobs? Cities with the most Full Time Linear Algebra job openings:
What are the most commonly searched types of Linear Algebra jobs? The most popular types of Linear Algebra jobs are:
What job categories do people searching Full Time Linear Algebra jobs look for? The top searched job categories for Full Time Linear Algebra jobs are:
Full Time Linear Algebra jobs near you
Infographic showing various Full Time Linear Algebra job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $59,999 per year, or $28.8 per hour.

New Grad Full-Time Quantitative Researcher

WallStreetQuants

New York, NY • On-site

Full-time

This job post has expired 7 days ago. Applications are no longer accepted.

Job description

About the Role

An NYC based hedge fund is seeking a highly motivated and intellectually curious New Grad Quantitative Researcher to join the team full time. This role is ideal for recent graduates who enjoy solving complex problems using mathematics, statistics, programming, and data-driven analysis.

As a Quantitative Researcher, you will work at the intersection of financial markets, statistical modeling, and technology. You will collaborate with traders, developers, and other researchers to identify patterns in market data, develop predictive models, test trading hypotheses, and support the creation of quantitative strategies.

This is an excellent opportunity for a new graduate who is analytical, creative, and excited to apply rigorous research methods to real-world financial markets.

Requirements

Responsibilities
  • Conduct quantitative research to identify signals, patterns, and inefficiencies in financial markets.
  • Analyze large and complex datasets, including market data, alternative data, and time-series data.
  • Develop, test, and refine statistical models, predictive signals, and trading strategies.
  • Design and run backtests, simulations, and experiments to evaluate research ideas.
  • Collaborate with traders and developers to translate research findings into production-ready tools and strategies.
  • Monitor model performance and contribute to ongoing strategy improvement.
  • Apply techniques from statistics, machine learning, optimization, probability, and econometrics to solve trading-related problems.
  • Present research findings clearly to technical and non-technical stakeholders.
  • Stay current on market behavior, quantitative methods, and emerging research relevant to trading and investing.
Qualifications
  • Recent graduate or upcoming graduate from a Bachelor’s, Master’s, PhD, or equivalent program.
  • Degree or strong demonstrated experience in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Physics, Economics, Finance, Data Science, Operations Research, or a related discipline.
  • Strong foundation in probability, statistics, linear algebra, optimization, or machine learning.
  • Programming experience in Python, R, C++, Java, Julia, MATLAB, or a similar language.
  • Experience working with data through coursework, research, internships, projects, or independent study.
  • Strong analytical thinking, problem-solving ability, and attention to detail.
  • Ability to communicate complex ideas clearly and work collaboratively across teams.
  • Interest in financial markets, trading, investing, or data-driven decision-making.
Preferred Qualifications
  • Research, internship, or project experience involving statistical modeling, machine learning, time-series analysis, forecasting, optimization, or quantitative finance.
  • Experience with Python data science libraries such as pandas, NumPy, SciPy, scikit-learn, PyTorch, TensorFlow, or statsmodels.
  • Familiarity with SQL, large-scale data processing, cloud tools, or distributed computing.
  • Exposure to financial instruments such as equities, futures, options, fixed income, FX, commodities, or digital assets.
  • Experience with backtesting, simulation, portfolio construction, or risk modeling.
  • Participation in math competitions, programming competitions, research publications, Kaggle, hackathons, trading competitions, poker, chess, or other analytical competitions.

Benefits

What We Offer
  • Full-time role designed for new graduates.
  • Structured training and mentorship from experienced quantitative researchers, traders, and engineers.
  • Opportunity to work on impactful research used in real-time trading and investment decisions.
  • Exposure to financial markets, strategy development, data science, and trading infrastructure.
  • A collaborative, intellectually rigorous environment where research quality and strong ideas are valued.
  • Early ownership of meaningful research projects.
  • Competitive compensation and benefits.