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Modelling Simulation Jobs in Maryland (NOW HIRING)

Sbdinc

Model Based Controls Engineer - Motors

Towson, MD · Hybrid

$90K - $144K/yr

Documenting control strategies, simulation results, and validation processes specific to Electrical ... Knowledge of modelling of Lithium-ion battery system is a plus. The Details: You'llreceive a ...

Sierra Nevada Corporation

Sr Systems Engineer

Hagerstown, MD · On-site

$103K - $141K/yr

Expert proficiency with Systems modeling and simulation tools. * Extensive technical leadership ... Advanced Experience with requirements management and system modelling tools, such as, Cameo, MATLAB.

Sierra Nevada Corporation

Sr Systems Engineer

Hagerstown, MD · On-site

$103K - $141K/yr

Expert proficiency with Systems modeling and simulation tools. * Extensive technical leadership ... Advanced Experience with requirements management and system modelling tools, such as, Cameo, MATLAB.

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Modelling Simulation information

What is the difference between Modelling Simulation vs Data Analyst?

AspectModelling SimulationData Analyst
Required CredentialsBachelor's or higher in Engineering, Mathematics, or related fields; often certifications in simulation softwareBachelor's or higher in Statistics, Mathematics, or related fields; certifications in data analysis tools
Work EnvironmentEngineering labs, research centers, or software development teamsBusiness offices, data centers, or consulting firms
Industry UsageManufacturing, aerospace, automotive, and engineering sectorsFinance, marketing, healthcare, and technology sectors
Common Search/ComparisonYesYes

Modelling Simulation and Data Analyst roles share overlapping skills in data handling and analytical thinking. However, Modelling Simulation focuses on creating and testing models to predict system behavior, often in engineering contexts. Data Analysts interpret data to inform business decisions. Both roles require strong technical skills, but their applications and industries differ significantly.

How to become a modeling and simulation engineer?

To become a modeling and simulation engineer, typically a bachelor's degree in engineering, computer science, or a related field is required, with advanced roles often requiring a master's or Ph.D. in a specialized area. Skills in programming languages such as C++, Python, or MATLAB, along with knowledge of simulation tools and systems modeling, are essential. Gaining experience through internships, certifications, or project work can also improve job prospects in this field.

Is modeling simulation a high paying job?

Modeling and simulation jobs are generally considered well-paying, especially for roles requiring advanced technical skills, programming, and knowledge of specialized software. Salaries vary based on experience, industry, and location, but professionals in this field often earn above average wages compared to other engineering or technical roles.

What are popular job titles related to Modelling Simulation jobs in Maryland?

For Modelling Simulation jobs in Maryland, the most frequently searched job titles are:

What job categories do people searching Modelling Simulation jobs in Maryland look for?

The top searched job categories for Modelling Simulation jobs in Maryland are:

Modelling Simulation jobs near you
Infographic showing various Modelling Simulation job openings in Maryland as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

Data Scientist - Financial Services Lab

McKinsey & Company

Lisbon, MD • On-site

Full-time

Posted 16 days ago

McKinsey & Company rating

8.5

Company rating: 8.5 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

20th of 72 rated business consultants

Job description

Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You've come to the right place.
YOUR IMPACT
You will apply advanced analytics techniques including predictive modelling, geospatial analysis, generative AI, optimization, and simulation to large-scale datasets at some of the world's most influential institutions.
You will partner with client teams across project settings to drive and produce week-one analyses and enable quick-turn analytics client development work. Many of these analyses will be used to develop solutions and products to craft reusable data-driven insights.
You will become an advocate for the use of data and analytics, guiding teams on the proper selection of datasets and analytic strategies to ensure we increase the value of impact we deliver to our clients. This will enable collaboration across other practices, analytics groups, and technical teams to ensure efforts are synergistic and cutting-edge.
You will help to maintain and deliver a compelling portrayal of McKinsey's data ecosystem and capabilities to clients and internal stakeholders. As well as drive awareness of the firm's policies related to data risk and refine/operationalize KPIs.
YOUR GROWTH
Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.
In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues-at all levels-will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won't find anywhere else.
When you join us, you will have:
  • Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
  • A voice that matters: From day one, we value your ideas and contributions. You'll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
  • Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm's diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you'll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
  • World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.

YOUR QUALIFICATIONS AND SKILLS
  • Master's degree in quantitative fields such as Mathematics, Computer Science, Engineering, Physics, or a related discipline
  • 2+ years of professional experience in data science, data engineering, or a closely related field
  • Experience with data engineering practices including ETL pipelines, orchestration tools such as Airflow, and big data platforms like Databricks; hands-on experience with data modelling techniques (e.g., 3NF, data vault, etc.), ability to work with both structured and unstructured data
  • Strong applied data science skills with experience in supervised and unsupervised learning, time series forecasting, clustering, optimization, geospatial modeling, and generative AI; familiarity with libraries such as scikit-learn, XGBoost, LightGBM, PyTorch, Hugging Face Transformers, and pandas
  • Solid engineering capabilities in Python and JavaScript, with hands-on experience building and operationalizing solutions using FastAPI and React
  • Comfortable working with Git, CI/CD tools, and modern development workflows
  • Hands-on experience with large language models (LLMs) and agentic AI, including prompt engineering, retrieval-augmented generation (RAG), tool/function calling, multi-agent workflows, evaluation, and productionizing LLM-powered applications
  • Familiarity with frameworks such as LangChain, LangGraph, LlamaIndex, and major model APIs
  • Familiarity with Azure cloud services; experience with Kubernetes, Docker, and distributed computing frameworks is a plus
  • Highly inquisitive and creative problem-solver with a passion for turning data into actionable insight
  • Entrepreneurial and self-starting mindset, comfortable navigating ambiguity in a fast-paced, dynamic environment
  • Collaborative, professional, and team-oriented, with a strong sense of ownership and service
  • Strong communication skills with the ability to convey complex technical topics to both technical and non-technical audiences

Please review the additional requirements regarding essential job functions of McKinsey colleagues.
Our unwavering commitment to integrity drives everything we do, guiding us to always act in the best interests of our clients, our people, and the communities we serve.

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