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Data Science Co Op Jobs in Silver Spring, MD (NOW HIRING)

Blend360

Data Science Manager

Columbia, MD · On-site

$125K - $160K/yr

Company Description Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission ...

Blend360

Data Science Manager

Columbia, MD

Company Description Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission ...

Blend360

Data Science Manager

Columbia, MD · On-site

$125K - $160K/yr

Company Description Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission ...

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Showing results 1-20

All JobsData Science Co Op JobsData Science Co Op Jobs in Silver Spring, MD

Data Science Co Op information

See Silver Spring, MD salary details

$38.8K

$126.9K

$203.1K

How much do data science co op jobs pay per year?

As of Jun 17, 2026, the average yearly pay for data science co op in Silver Spring, MD is $126,884.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,800.00 and $140,600.00 per year, depending on experience, location, and employer.

What is the 80 20 rule in data science?

The 80/20 rule in data science suggests that roughly 80% of the results come from 20% of the efforts or data. Data scientists often use this principle to focus on the most impactful features, data subsets, or models to improve efficiency and outcomes in their analyses.

Is 40 too late for data science?

Data science co-ops and entry-level roles often value skills and relevant experience over age, so starting a career at 40 is not too late. Many professionals successfully transition into data science later in life by learning programming languages like Python or R, gaining certifications, and building portfolios. Age should not be a barrier if you develop the necessary technical skills and stay current with industry tools and trends.

Which is better, DS or CS?

Data Science Co-ops focus on analyzing data, building models, and applying statistical tools, often requiring skills in programming, statistics, and data visualization. Computer Science roles emphasize software development, algorithms, and system design, typically involving programming languages like Java or C++. Both fields offer valuable career paths, but the choice depends on your interests in data analysis versus software engineering.

What kinds of projects or tasks can I expect to work on as a Data Science Co Op?

As a Data Science Co Op, you may be involved in a variety of projects such as data cleaning, exploratory data analysis, building predictive models, or generating data visualizations to support business decisions. You’ll often work alongside more experienced data scientists, analysts, and cross-functional teams to collaboratively solve real-world problems using data. This role typically emphasizes hands-on learning and practical application of analytical techniques, offering a great opportunity to develop your technical and communication skills. In addition, you may participate in regular meetings, present findings, and contribute to ongoing research or product development initiatives.

What are the key skills and qualifications needed to thrive in the Data Science Co Op position, and why are they important?

To succeed as a Data Science Co Op, you should have a solid understanding of statistics, data analysis, and programming, typically gained through coursework or relevant experience in computer science, mathematics, or related fields. Familiarity with tools such as Python or R, SQL databases, and data visualization libraries is highly valuable, and experience with machine learning platforms or certifications can be advantageous. Effective communication, problem-solving, and a collaborative mindset help you excel in team-oriented, fast-paced environments. These competencies are crucial for analyzing complex datasets, delivering actionable insights, and supporting business decision-making.

Is 30 too late for data science?

Data science Co Op roles often target students or early-career individuals, but age is not a strict barrier. Many professionals transition into data science later in their careers by acquiring relevant skills such as programming, statistics, and tools like Python or R, and completing certifications or projects to demonstrate expertise.

What is a Data Science Co Op job?

A Data Science Co-Op is a temporary, structured work experience program for students or early-career professionals to apply data science skills in a real-world setting. Co-Ops typically last several months and involve tasks such as data analysis, machine learning model development, and visualization. Participants work closely with data teams, gaining hands-on experience with tools like Python, SQL, and cloud platforms. Unlike internships, Co-Op positions may be full-time for a semester and often offer deeper engagement with projects. This experience helps build technical skills, industry knowledge, and professional connections for future career opportunities.

What are the most commonly searched types of Data Science jobs in Silver Spring, MD? The most popular types of Data Science jobs in Silver Spring, MD are:
What job categories do people searching Data Science Co Op jobs in Silver Spring, MD look for? The top searched job categories for Data Science Co Op jobs in Silver Spring, MD are:
What cities near Silver Spring, MD are hiring for Data Science Co Op jobs? Cities near Silver Spring, MD with the most Data Science Co Op job openings:
Data Science Co Op jobs near you
Infographic showing various Data Science Co Op job openings in Silver Spring, MD as of June 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $126,884 per year, or $61 per hour.
Internship/Co-op, Building Technology Fall 2026

Internship/Co-op, Building Technology Fall 2026

Simpson Gumpertz & Heger

Washington, DC • On-site

$19 - $24.75/hr

Other

Posted 2 days ago

Job description

We want someone passionate about building enclosure engineering who wants to gain invaluable experience.

Simpson Gumpertz & Heger (SGH) is seeking current students for a Fall 2026 Internship and/or Co-op in our Washington, D.C. office.

As an Intern or Co-op, you will work side-by-side with industry-leading experts in the office and in the field to gain hands-on experience while applying classroom knowledge to real-world challenges.

 What You'll Be Doing:

  • Assist with construction monitoring, field investigations, condition assessments, construction observations as well as project drafting, and analysis, and site inspections.
  • Analyze materials, support our laboratory staff, review and coordinate test protocols, design and construct testing apparatus, perform tests, and analyze test data.
  • Collaborate with SGH engineers to perform reconnaissance on existing buildings, conduct field tests, or monitor construction in progress.
  • Organize field data and assist with research to facilitate analysis, problem solving, and repair design.
  • Perform analysis under the guidance of licensed professionals using a combination of hand calculations and analysis software.
  • Assist with preparation of client deliverables, including construction documents, specifications, detail sketches, and written reports.
  • Work may include travel and working from heights.

What You'll Need:

  • Students should have an interest in building design and construction, civil and or structural engineering, materials science, architecture, and architectural engineering.
  • Students should be enrolled in in a civil/structural, building science, material architecture, or architectural engineering program.
  • Maintain high grades in their studies, interested in learning through hands-on work experience in a consulting engineering environment.
  • Enthusiastic about the challenges associated with the development of sophisticated engineering work product in an atmosphere of high professionalism. 
  • Strong communication skills.

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