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Internship Data Science Physics Jobs in Atlanta, GA

Lead Data Scientist

Dallas, GA · On-site

$161 - $270/hr

Education/Experience Master's degree (MS/MA) required from an accredited University in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics. 5+ years of ...

Data Scientist

Atlanta, GA · On-site

$95 - $110/hr

What You Will Bring: * 0-2 years of experience in data science, analytics, machine learning, or a related field, including internships, research, senior projects, or meaningful independent projects.

Lead Data Scientist

Atlanta, GA · On-site

$160K - $270K/yr

Master's degree (MS/MA) required from an accredited University in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics. 5+ years of related experience.

Master's degree (MS/MA) required from an accredited University in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics. 5+ years of related experience.

Showing results 21-40

Internship Data Science Physics information

See Atlanta, GA salary details

$11

$21

$40

How much do internship data science physics jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for internship data science physics in Atlanta, GA is $21.64, according to ZipRecruiter salary data. Most workers in this role earn between $16.63 and $23.56 per hour, depending on experience, location, and employer.

What is an internship data science physics?

Internship Data Science Physics positions are temporary roles designed for students or recent graduates with a background in physics who are interested in applying data science techniques to solve scientific and analytical problems. These internships typically involve working with large datasets, performing statistical analyses, building models, and interpreting results within a physics-related context. Interns gain hands-on experience with programming languages like Python or R, machine learning tools, and data visualization methods, often contributing to research or product development teams. These roles help bridge academic knowledge in physics with practical data science skills, preparing interns for careers in research, technology, or industry.

What types of projects or tasks can I expect to work on during an internship data science physics?

As a Data Science Physics intern, you can expect to work on projects that involve analyzing large datasets derived from physical experiments or simulations, developing predictive models, and visualizing complex phenomena. Typical tasks might include cleaning and preprocessing data, applying statistical or machine learning techniques, and collaborating with researchers to interpret results. You may also assist in automating data workflows or contributing to scientific publications, providing a dynamic and collaborative environment that bridges data science and physics.

What are the key skills and qualifications needed to thrive as an internship data science physics, and why are they important?

To thrive as an Internship Data Science Physics, you need a solid grounding in physics, mathematics, and programming, typically supported by progress toward a relevant degree. Familiarity with data analysis tools such as Python, MATLAB, or R, and experience using statistical or machine learning libraries are commonly expected. Strong problem-solving, analytical thinking, and effective communication skills help interns stand out in team-based research environments. These competencies ensure you can effectively analyze complex data, contribute to scientific discoveries, and present insights clearly.

What is the difference between Internship Data Science Physics vs Data Analyst Intern?

AspectInternship Data Science PhysicsData Analyst Intern
Required SkillsProgramming, data analysis, physics concepts, statistical methodsData analysis, Excel, SQL, visualization tools
Work EnvironmentResearch labs, tech companies, academiaBusiness, finance, marketing departments
Industry UsageResearch, scientific computing, tech innovationBusiness intelligence, reporting, decision-making

Internship Data Science Physics focuses on applying data science skills within physics and research contexts, often involving scientific computing and experimental data. In contrast, Data Analyst Internships are centered on analyzing business data, creating reports, and supporting decision-making processes. Both roles require analytical skills and familiarity with data tools, but their environments and applications differ significantly.

What are the most commonly searched types of Data Science Physics jobs in Atlanta, GA?

The most popular types of Data Science Physics jobs in Atlanta, GA are:

What job categories do people searching Internship Data Science Physics jobs in Atlanta, GA look for?

The top searched job categories for Internship Data Science Physics jobs in Atlanta, GA are:

What cities near Atlanta, GA are hiring for Internship Data Science Physics jobs?

Cities near Atlanta, GA with the most Internship Data Science Physics job openings:

Infographic showing various Internship Data Science Physics job openings in Atlanta, GA as of August 2026, with employment types broken down into 16% Internship, 71% Full Time, 7% Part Time, and 6% Contract. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $45,014 per year, or $21.6 per hour.

$161 - $270/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired 2 days ago. Applications are no longer accepted.


Key responsibilities

  • Collect, clean, and preprocess data from various sources to ensure quality for analysis.

  • Create features, conduct exploratory data analysis, and develop machine learning models, including hyperparameter tuning and model evaluation.

  • Build visualizations and reports for stakeholders, and develop and implement generative AI models and techniques.


Cricket Wireless rating

4.3

Company rating: 4.3 out of 10

Based on 127 frontline employees who took The Breakroom Quiz

98th of 101 rated telecommunications companies


Job description

This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted. No relocation is offered.

Overall Purpose

Translate business problems into actionable insights through a comprehensive workflow involving coding, data extraction, cleansing, feature engineering, exploratory data analysis, model creation and tuning, visualization, and deployment, leveraging statistical analysis, machine learning, and big data technologies to drive informed decision-making and innovation.

Key Roles and Responsibilities
  • Data Extraction and Preparation: Collect data from various structured and unstructured sources (datalakes, databases, data warehouses, on cloud, internal, external) and ensure its quality for analysis through cleaning and preprocessing. Designs, builds, and analyzes large (e.g. 100’s of Terabytes or higher as technology advances) and complex data sets while thinking strategically about data use and data design. Tools can include
  • Coding Solutions, Algorithms and Feature Engineering: Create relevant features and conduct exploratory data analysis. Codes solutions following typical workflow; data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyper-parameter tuning, model interpretation, model retraining, business process and/or system implementations, high level proof of concept and trials, visualization, deployment to production, post deployment ML ops monitoring/diagnosis/resolutions. Coding proficiency required in at least one data science language (Python, R, Scala, etc.), as well as expertise with modern ML packages and libraries (Spark, SciKitLearn, Pandas, PyTorch, TidyVerse, Tensorflow, Keras, Shiny, and/or AutoML tools).
  • Model Development, Deployment and Optimization: Build, evaluate, and optimize machine learning models through hyperparameter tuning. Implement models into production, continuously monitor their performance, and ensure they remain explainable and reliable to minimize model decay. Ability to develop custom Machine Learning (ML). Highly proficient in the full AI workflow such as (1) data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyperparameter tuning, model interpretation, model retraining and (2) Uses concepts like mlflow to log metrics. Well-versed in Interactive Development Environments (IDEs) such as Databricks Workspaces or Visual Studio Code. Proficiency in algorithm categories such as Supervised Learning, Unsupervised Learning, Optimization Algorithms, Deep Learning, AI-Computer Vision, Natural Language Processing, Deep Reinforcement Learning, Search Algorithms, and AI- Knowledge Graphs.
  • Visualization and Collaboration: Create visualizations and reports for stakeholders while working closely with cross-functional teams to align efforts with business objectives. Can utilize advanced coding methods to produce visualizations (e.g. ggplot, D3.js, etc.).
  • Generative AI: Develop and implement generative AI models, focusing on creating new content or augmenting existing data. Generative Models-Understanding of GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers. Fine-Tuning-Techniques for adapting pre-trained models to specific tasks using smaller, task-specific datasets. Agentics-Understanding of agentic architecture, concepts and optimization of solutions. Prompt Engineering-Crafting effective prompts to guide generative models in producing desired outputs. Retrieval-Augmented Generation (RAG)-Combining generative models with retrieval systems to enhance performance and relevance. Text Generation-Proficiency in using models like GPT-3/4 for generating human-like text. Image Generation-Familiarity with tools like DALL-E and Stable Diffusion for creating images from text descriptions.
Job Contribution

An experienced professional, recognized as an expert, creatively resolving complex issues with broad and in-depth knowledge. Leads significant projects with strategic autonomy, influencing executive decisions. Mentors less experienced staff, implements long-term plans impacting the organization, and frequently collaborates with senior leadership.

Supervisor

No TCP Career Step Differentiator: Performs very complex data science work, builds complex business models, and makes recommendations that impact multiple organizations, lines of the business, etc.

Education/Experience

Master's degree (MS/MA) required from an accredited University in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics. 5+ years of related experience. Certification is required in some areas.

Our Lead Data Scientist earn between $160,900 - $270,400.

Not to mention all the other amazing rewards that working at AT&T offers. Individual starting salary within this range may depend on geography, experience, expertise, and education/training.

Benefits and Perks
  • Medical/Dental/Vision coverage
  • 401(k) plan
  • Tuition reimbursement program
  • Paid Time Off and Holidays (based on date of hire, at least 23 days of vacation each year and 9 company-designated holidays)
  • Paid Parental Leave
  • Paid Caregiver Leave
  • Additional sick leave beyond what state and local law require may be available but is unprotected
  • Adoption Reimbursement
  • Disability Benefits (short term and long term)
  • Life and Accidental Death Insurance
  • Supplemental benefit programs: critical illness/accident hospital indemnity/group legal
  • Employee Assistance Programs (EAP)
  • Extensive employee wellness programs
  • Employee discounts up to 50% off on eligible AT&T mobility plans and accessories, AT&T internet (and fiber where available) and AT&T phone

Relevant Material Job Duties for which Criminal History may have a direct adverse, and negative relationship potentially resulting in the withdrawal of the Conditional Offer of Employment Contact with Customers/Candidates/Clients Safety Sensitivity (Vehicle/Tool/Machine Operation - if applicable) Handling/Proximity to Sensitive Information

Our Lead Data Scientist jobs earn between $160,900.00 - $270,400.00 USD Annual. Not to mention all the other amazing rewards that working at AT&T offers. Individual starting salary within this range may depend on geography, experience, expertise, and education/training. Joining our team comes with amazing perks and benefits: Medical/Dental/Vision coverage 401(k) plan Tuition reimbursement program Paid Time Off and Holidays (based on date of hire, at least 23 days of vacation each year and 9 company-designated holidays) Paid Parental Leave Paid Caregiver Leave Additional sick leave beyond what state and local law require may be available but is unprotected Adoption Reimbursement Disability Benefits (short term and long term) Life and Accidental Death Insurance Supplemental benefit programs: critical illness/accident hospital indemnity/group legal Employee Assistance Programs (EAP) Extensive employee wellness programs Employee discounts up to 50% off on eligible AT&T mobility plans and accessories, AT&T internet (and fiber where available) and AT&T phone

Weekly Hours: 40 Time Type: Regular Location: Atlanta, Georgia, Dallas, Texas, El Segundo, California Salary Range: $160,900.00 - $270,400.00

AT&T and its subsidiaries are committed to equal employment opportunity. All hiring, promotion, and other employment decisions remain merit-based and free from discrimination on the basis of race, color, religion, religious creed, national origin, ancestry, age, sex, sexual orientation, gender, gender identity, gender expression, physical disability, mental disability, pregnancy, medical condition, genetic information, marital status, citizenship status, military status, veteran status, or any other characteristic protected by federal, state, or local laws. In addition, AT&T will provide reasonable accommodations to qualified individuals with disabilities. AT&T is a fair chance employer and does not initiate a background check until an offer is made.

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