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Numerical Methods Jobs in Maryland (NOW HIRING)

Data Scientist

Fort George G Meade, MD · On-site

$125 - $150/hr

... g. numerical methods, graph theory), artificial intelligence, workflow and reproducibility, data management and curation, data modeling and assessment (e.g., model selection, evaluation, and ...

Showing results 21-40

Numerical Methods information

See Maryland salary details

$26.7K

$55.1K

$58.7K

How much do numerical methods jobs pay per year?

As of Sep 9, 2026, the average yearly pay for numerical methods in Maryland is $55,052.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,300.00 and $57,700.00 per year, depending on experience, location, and employer.

What is a numerical methods job?

A Numerical Methods job involves developing, analyzing, and implementing algorithms to solve mathematical problems numerically. Professionals in this field work on optimizing computations for engineering, physics, finance, and other scientific applications. They use programming languages like Python, MATLAB, or C++ to create efficient and accurate numerical solutions. These jobs are common in industries such as aerospace, data science, and applied mathematics, where analytical models are essential for decision-making and simulations.

What are some common projects or problems handled by professionals specializing in numerical methods?

Professionals specializing in Numerical Methods typically work on projects involving the development and implementation of algorithms to solve mathematical models for engineering, physics, finance, or data science applications. Common responsibilities include simulating physical systems, optimizing processes, or analyzing large data sets using numerical techniques. These roles often involve close collaboration with engineers, scientists, or analysts to translate real-world problems into computational form and validate results against experimental data. The projects are diverse, providing ample opportunities to deepen expertise in both theoretical and practical aspects of numerical analysis.

What are the key skills and qualifications needed to thrive in the numerical methods position, and why are they important?

To thrive in a Numerical Methods role, a strong background in applied mathematics, computational modeling, and problem-solving is essential, often supported by a degree in mathematics, engineering, or a related field. Proficiency with programming languages such as MATLAB, Python, or FORTRAN, and experience with numerical analysis software, are commonly required. Analytical thinking, teamwork, and effective communication are vital soft skills to excel in this position. These competencies are crucial for accurately analyzing complex data and collaborating across multidisciplinary teams to develop reliable computational solutions.

What do numerical methods do?

Numerical methods are techniques used by professionals in computational fields to approximate solutions to mathematical problems that are difficult or impossible to solve analytically. They involve algorithms and software tools to perform calculations efficiently, often used in engineering, science, and data analysis to model and simulate real-world systems.

What are popular job titles related to Numerical Methods jobs in Maryland?

For Numerical Methods jobs in Maryland, the most frequently searched job titles are:

Infographic showing various Numerical Methods job openings in Maryland as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $55,052 per year, or $26.5 per hour.

Data Scientist - multiple levels - CLEARANCE and POLYGRAPH REQUIRED

Laurel, MD • On-site

Constellation Technologies, Inc
IT Services • 11 - 50 employees

Full-time

Re-posted 17 days ago


Job description

Job Summary:
Constellation Technologies, Inc. is a company that specializes in advanced data solutions, and they are seeking a Data Scientist with a TS/SCI security clearance and polygraph. The role involves designing and implementing machine learning and data science algorithms, analyzing large datasets, and effectively communicating complex technical information to various audiences.
Responsibilities:
• Devise strategies for extracting meaning and value from large datasets.
• Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge.
• Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent to Agency data holdings.
• Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data.
• Effectively communicate complex technical information to non-technical audiences.
• Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting Agency collection, processing, storage and analytic capabilities and limitations.
Qualifications:
Required:
• Must be a US Citizen
• Must have TS/SCI clearance w/ active polygraph
• This position is open to multiple levels of years of experience; two (02) years within the last five (05) years must be directly related to the job you are applying for:
• Level 04 requires a minimum seventeen (17) years of experience w/ Degree
• Level 03 requires a minimum twelve (12) years of experience w/ Degree
• Level 02 requires a minimum five (05) years of experience w/ Degree
• Degree in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science. A degree in a related field (e.g., Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g., physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e., behavioral, social, and life) may be considered if it includes a concentration of coursework (typically 5 or more courses) in advanced mathematics (typically 300 level or higher; such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g., algorithms, programming, data structures, data mining, artificial intelligence). College-level Algebra or other math courses intended to meet a basic college level requirement, or upper-level math courses designated as elementary or basic do not count.
• Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g., Python) and skill in at least one mid-level language (e.g. C)), data mining, advanced statistical analysis (e.g. statistical foundations of machine learning, statistical approaches to missing data, time series), advanced mathematical foundations (e.g. numerical methods, graph theory), artificial intelligence, workflow and reproducibility, data management and curation, data modeling and assessment (e.g. model selection, evaluation, and sensitivity.
• Employ some combination (2 or more) of the following areas: Foundations (Mathematical, Computational, Statistical); Data Processing (Data management and curation, data description and visualization, workflow, and reproducibility); Modeling, Inference, and Prediction (Data modeling and assessment, domain-specific considerations).
• Devise strategies for extracting meaning and value from large datasets.
• Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge.
• Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent to Agency data holdings.
• Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data.
• Effectively communicate complex technical information to non-technical audiences.
• Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting Agency collection, processing, storage and analytic capabilities and limitations.
Preferred:
• Fully Cleared polygraph is preferred
• Knowledge of working with Big Data, dataflows, Machine Learning/Artificial Intelligence familiarity.
• Analytics in GME, Jupyter notebooks, and Spark.
Company:
Constellation Technologies, Inc. Founded in 2008, the company is headquartered in Columbia, USA, with a team of 51-200 employees. The company is currently Growth Stage.