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Intern Data Scientist Machine Learning Jobs in Reisterstown, MD

MANTECH seeks a motivated, career and customer-oriented Data Scientist in Fort Meade, MD , to drive ... machine learning into mission operations. Responsibilities include but are not limited to:

New

MANTECH seeks a motivated, career and customer-oriented Data Scientist in Fort Meade, MD , to drive ... machine learning into mission operations. Responsibilities include but are not limited to:

New

Data Scientist

Fort George G Meade, MD · On-site

$100 - $130/hr

This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and ... Implement core data science capabilities, such as entity resolution, classification, clustering, or ...

MANTECH seeks a motivated, career and customer-oriented Data Scientist in Fort Meade, MD , to drive ... Practical knowledge of advanced statistical modeling and foundational machine learning techniques ...

New

Data Scientist

Fort George G Meade, MD · On-site

$141K - $236K/yr

MANTECH seeks a motivated, career and customer-oriented Data Scientist in Fort Meade, MD , to drive ... Practical knowledge of advanced statistical modeling and foundational machine learning techniques ...

New

Data Scientist Location: Baltimore, MD (Onsite) Hiring Type: Contract Job Summary: We are seeking a ... Design, develop, and deploy machine learning and NLP models for text-based applications. * Work ...

Data Scientist, Senior

Edgewood, MD · On-site

$99 - $225/hr

You Have * 4+ years of experience with data science, machine learning, data engineering, or data analytics * 1+ years of experience using Palantir Foundry for application development * Experience ...

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Intern Data Scientist Machine Learning information

See Reisterstown, MD salary details

$23.8K

$39.8K

$82.2K

How much do intern data scientist machine learning jobs pay per year?

As of Aug 29, 2026, the average yearly pay for intern data scientist machine learning in Reisterstown, MD is $39,757.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,300.00 and $42,900.00 per year, depending on experience, location, and employer.

What does an intern data scientist machine learning do?

An Intern Data Scientist in Machine Learning assists in analyzing large datasets, building predictive models, and extracting insights to support business decisions. They often work under the guidance of experienced data scientists to clean data, implement machine learning algorithms, and evaluate model performance. Their responsibilities may also include data visualization and reporting findings to team members. This role provides hands-on experience with real-world data science problems and tools, helping interns develop essential technical and analytical skills.

What types of projects and responsibilities can an intern data scientist machine learning expect to work on?

As an Intern Data Scientist focused on Machine Learning, you will often assist in tasks such as data cleaning, feature engineering, and developing or testing machine learning models under the supervision of senior team members. You may also be involved in exploratory data analysis and help interpret model results to provide actionable insights. Interns typically collaborate closely with data engineers, analysts, and software developers, gaining exposure to end-to-end machine learning pipelines. This hands-on experience provides valuable learning opportunities and helps build the foundational skills needed for future roles in data science.

What are the key skills and qualifications needed to thrive as an intern data scientist machine learning, and why are they important?

To thrive as an Intern Data Scientist (Machine Learning), you need a solid understanding of statistics, programming skills (typically in Python or R), and foundational knowledge of machine learning algorithms, often supported by coursework or relevant projects. Familiarity with tools like scikit-learn, TensorFlow, Jupyter notebooks, and version control systems (e.g., Git) is commonly expected. Strong analytical thinking, curiosity, and effective communication skills help you interpret data insights and work collaboratively within a team. These abilities are crucial for translating data into actionable solutions and contributing to impactful machine learning projects.

What is the difference between Intern Data Scientist Machine Learning vs Intern Data Analyst?

AspectIntern Data Scientist Machine LearningIntern Data Analyst
Required SkillsBasic programming, statistics, machine learning conceptsData analysis, Excel, SQL, visualization tools
Work EnvironmentResearch-focused, model development, algorithm testingData cleaning, reporting, dashboard creation
Common Industry UsageTech, finance, healthcareRetail, marketing, finance

Intern Data Scientist Machine Learning roles focus on developing and testing machine learning models, requiring knowledge of algorithms and programming. Intern Data Analyst positions emphasize data cleaning, analysis, and visualization. Both roles are entry-level but differ in technical depth and project focus, catering to different career paths within data-driven industries.

What are popular job titles related to Intern Data Scientist Machine Learning jobs in Reisterstown, MD?

For Intern Data Scientist Machine Learning jobs in Reisterstown, MD, the most frequently searched job titles are:

What job categories do people searching Intern Data Scientist Machine Learning jobs in Reisterstown, MD look for?

The top searched job categories for Intern Data Scientist Machine Learning jobs in Reisterstown, MD are:

What cities near Reisterstown, MD are hiring for Intern Data Scientist Machine Learning jobs?

Cities near Reisterstown, MD with the most Intern Data Scientist Machine Learning job openings:

Data Scientist / Machine Learning (TS SCI + Poly is Required)

Aperio Global

Fort George G Meade, MD

Full-time

Posted 10 days ago


Job description

Aperio Global is seeking a Data Scientist to develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.

Overview: 

Level 1

Produce data visualizations that provide insight into dataset structure and meaning.
Collaborate with subject matters experts (SMEs) to identify important information in raw data
and develop scripts that extract this information from a variety of data formats (e.g., SQL tables,
structured metadata, network logs).
Incorporate SME input into feature vectors suitable for analytic development and testing.
Translate customer qualitative analysis process and goals into quantitative formulations that are coded into software prototypes.
Develop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics.
Develop statistical tests to make data-driven recommendations and decisions

Level 2

Develop experiments to collect data or models to simulate data when required data are unavailable.
Develop feature vectors for input into machine learning algorithms.
Identify the most appropriate algorithm for a given dataset and tune input and model parameters.
Evaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices).
Evaluate individual analytic efforts and make recommendations in the analytic development process.
Recommend solutions that can scale to large datasets.
Collaborate with software engineers, cloud developers, and appropriate stakeholders to develop production analytics.
Develop and train machine learning systems based on statistical analysis of data characteristics to support mission automation
Security Clearance Requirements:

This position requires all candidates to be U.S. Citizens and possess an active TS/SCI Security Clearance with a Polygraph.

Qualifications:

Requires a Bachelor's degree in a relevant discipline (e.g., statistics, mathematics, operations research, and engineering or computer science) from an accredited college or university, and four (4) years of experience analyzing datasets and developing analytics and two (2) year of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
A Master's degree in relevant discipline may be substituted for two (2) years of relevant experience analyzing datasets and developing analytics, and one (1) year of relevant experience programming with data analysis software such as R, Python, SAS, or MATLAB.
In lieu of a Bachelor's Degree, an additional four (4) years of relevant experience may be substituted for a total of eight (8) years of relevant experience analyzing datasets and developing analytics, and two (2) years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.

Level 2: 
A PhD in relevant discipline may be substituted for four (4) years relevant experience reducing the requirement to four (4) years of relevant experience analyzing datasets and developing analytics, and one (1) year of experience programming with data analysis software such as R, Python, SAS, or MATLAB.

Anticipated Salary Range; 
LEVEL 1     150-170  
LEVEL 2    170-190