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Applied Mathematics Computer Science Jobs in New Jersey

... science applications. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ... Familiar with applied mathematics curricula and common challenges such as translating physical ...

... science applications. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ... Familiar with applied mathematics curricula and common challenges such as translating physical ...

... science applications. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ... Familiar with applied mathematics curricula and common challenges such as translating physical ...

... science applications. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ... Familiar with applied mathematics curricula and common challenges such as translating physical ...

... science applications. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ... Familiar with applied mathematics curricula and common challenges such as translating physical ...

... science applications. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ... Familiar with applied mathematics curricula and common challenges such as translating physical ...

... science applications. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ... Familiar with applied mathematics curricula and common challenges such as translating physical ...

... science applications. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ... Familiar with applied mathematics curricula and common challenges such as translating physical ...

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Applied Mathematics Computer Science information

What is the difference between Applied Mathematics Computer Science vs Data Analyst?

AspectApplied Mathematics Computer ScienceData Analyst
Required CredentialsBachelor's or higher in applied math, computer science, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentResearch labs, tech companies, academiaBusiness, finance, healthcare, and marketing sectors
Employer & Industry UsageTech firms, research institutions, universitiesCorporations, consulting firms, government agencies
Common Search & ComparisonApplied Mathematics Computer Science vs Data Analyst

Applied Mathematics Computer Science focuses on developing algorithms, modeling, and computational techniques, often requiring programming and mathematical skills. Data Analysts interpret data to provide insights, primarily using statistical tools. While both roles involve data and programming, Applied Mathematics Computer Science emphasizes algorithm development and complex modeling, whereas Data Analysts focus on data interpretation and reporting.

What are popular job titles related to Applied Mathematics Computer Science jobs in New Jersey? For Applied Mathematics Computer Science jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching Applied Mathematics Computer Science jobs in New Jersey look for? The top searched job categories for Applied Mathematics Computer Science jobs in New Jersey are:
What cities in New Jersey are hiring for Applied Mathematics Computer Science jobs? Cities in New Jersey with the most Applied Mathematics Computer Science job openings:
Infographic showing various Applied Mathematics Computer Science job openings in New Jersey as of May 2026, with employment types broken down into 2% Internship, 4% As Needed, 83% Full Time, 9% Part Time, and 2% Contract. Highlights an 94% Physical, 4% Hybrid, and 2% Remote job distribution.

Full-time

Posted 4 days ago


Job description

Overview:
Summary
Key Responsibilities
• Formulate complex optimization problems (nonlinear, nonconvex, stochastic, constrained, multi-objective).
• Build advanced optimization pipelines using:
oSciPy Optimize, PySwarms, mystic, pymoo, Bayesian Optimization.
• Develop custom, complex solvers and hybrid algorithms leveraging open-source optimization frameworks.
• Implement objective functions, constraint models, surrogate models, and penalty formulations.
• Integrate optimization techniques into ML workflows (hyperparameter tuning, black-box optimization, surrogate modeling).
• Conduct convergence, sensitivity, robustness, and stability analysis of optimization methods.
• Scale optimization systems using Python, distributed computing, and numerical acceleration.
• Communicate complex mathematical concepts to cross-functional audiences.
Required Qualifications
• Masters/PhD in Operations Research, Applied Mathematics, Computer Science, Engineering, or related quantitative field.
• Expertise in nonlinear, global, evolutionary, and multi-objective optimization (e.g., NSGA-II/III, CMA-ES, DE).
• Strong knowledge of Bayesian Optimization and Gaussian Process modeling.
• Deep mathematical foundation (numerical methods, probability, linear algebra).
• Proficiency in the Python scientific ecosystem (NumPy, SciPy, pandas, scikit-learn).
• Demonstrated ability to design custom solvers for high-dimensional, ambiguous, or poorly behaved optimization landscapes.