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Python Intern Jobs in Newton, MA (NOW HIRING)

Data Science Intern Statistical Modeling & Marketing Measurement Remote | Internship | Full-time | ... Prepare and explore data using Python and SQL; perform data-quality checks, feature construction ...

Data Science Intern Statistical Modeling & Marketing Measurement Remote | Internship | Full-time | ... Prepare and explore data using Python and SQL; perform data-quality checks, feature construction ...

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Python Intern information

What does a Python intern do?

A Python Intern typically assists in developing, testing, and maintaining software applications using the Python programming language. They may work on tasks such as writing scripts, debugging code, automating processes, and collaborating with team members on various projects. Interns often gain hands-on experience with frameworks, libraries, and tools commonly used in Python development. The role is designed to help them build practical skills and prepare for a full-time career in software engineering.

What types of projects can a Python intern expect to work on during their internship?

As a Python Intern, you will typically be involved in supporting ongoing development projects, such as building automation scripts, data analysis tools, or assisting with backend web development. Interns often collaborate with software engineers, data scientists, or QA teams to contribute code, debug issues, and participate in code reviews. The scope of projects may vary by company, but most internships provide hands-on experience with real codebases, exposure to version control systems like Git, and opportunities to learn best practices from experienced mentors.

What are the key skills and qualifications needed to thrive as a Python intern, and why are they important?

To thrive as a Python Intern, you need a solid understanding of Python programming fundamentals, problem-solving ability, and typically a background in computer science or related coursework. Familiarity with version control systems like Git, basic knowledge of frameworks such as Django or Flask, and experience using code editors or IDEs are common technical requirements. Initiative, willingness to learn, and effective communication help interns stand out by enabling collaboration and adaptability in team environments. These skills ensure that interns can contribute effectively to projects, learn quickly, and integrate smoothly into professional development workflows.

What is the difference between Python Intern vs Python Developer?

AspectPython InternPython Developer
Required CredentialsTypically pursuing or recently completed a degree in computer science or related fieldProven experience, often with a degree or equivalent in computer science or related field
Work EnvironmentInternship programs, entry-level projects, supervised tasksFull-time roles, independent project work, team collaboration
Employer & Industry UsageTech companies, startups, educational institutionsTech firms, software companies, enterprise environments
Common Search & ComparisonEntry-level, learning, internship opportunitiesProfessional, full-time employment, career growth

The main difference between a Python Intern and a Python Developer lies in experience and responsibilities. Interns are usually students or recent graduates gaining initial exposure, working under supervision. Developers are experienced professionals responsible for designing, coding, and maintaining software solutions independently. Internships serve as a stepping stone toward becoming a full-fledged Python Developer.

What are the most commonly searched types of Python jobs in Newton, MA?

The most popular types of Python jobs in Newton, MA are:

What cities near Newton, MA are hiring for Python Intern jobs?

Cities near Newton, MA with the most Python Intern job openings:

Data Science Intern

Boston, MA โ€ข On-site, Remote

FocusKPI Inc.
Computing Infrastructure Providers, Data Processing, Web Hostingย โ€ขย 51 - 200 employees

Full-time

Posted 11 days ago


Job description

Data Science Intern
Statistical Modeling & Marketing Measurement
Remote | Internship | Full-time | 3 months
About the Role
We are looking for a curious and analytically minded Data Science Intern to support the development and evaluation of statistical and machine learning models for marketing measurement. This role is designed for someone with strong quantitative fundamentals who wants hands-on experience applying regression, model diagnostics, validation, and data analysis to real business problems. You will work closely with experienced data scientists, learn how modeling choices affect interpretation and business decisions, and contribute clean, reproducible analytical work.
Responsibilities
  • Support the development and evaluation of models including regression, time-series, and other statistical or machine learning approaches, with attention to predictive performance, stability, and interpretability.
  • Prepare and explore data using Python and SQL; perform data-quality checks, feature construction, descriptive analysis, and visualization to understand modeling inputs and outcomes.
  • Apply core model-validation techniques such as train/validation/test splits, cross-validation, baseline comparisons, and appropriate performance metrics.
  • Investigate common statistical issues including multicollinearity, overfitting, residual patterns, autocorrelation, heteroskedasticity, and unstable coefficients, with guidance from senior team members.
  • Test and compare reasonable modeling choices such as feature transformations, regularization settings, and model specifications, and summarize how these choices affect model results.
  • Interpret model outputs and connect technical findings to practical marketing or business questions while clearly stating assumptions and limitations.
  • Contribute to reproducible analytical workflows for model training, validation, sensitivity checks, and result comparison.
  • Write clear Python and SQL code and communicate methods, findings, assumptions, and open questions in a structured and understandable way.

Basic Qualifications
  • Strong foundation in statistics and regression: understanding of linear regression, key model assumptions, coefficient interpretation, regularization concepts, and basic statistical inference.
  • Solid quantitative fundamentals in probability, statistics, and linear algebra; familiarity with calculus or optimization concepts is helpful.
  • Working knowledge of Python for data analysis and modeling, including common data-science libraries; basic to intermediate SQL skills for data extraction and transformation.
  • Understanding of model evaluation: training versus validation data, cross-validation, common regression metrics, overfitting, and the importance of out-of-sample performance.
  • Ability to reason through modeling problems: investigate unexpected results, form hypotheses about root causes, test alternatives, and explain conclusions using evidence.
  • Clear communication skills: ability to explain analytical methods, assumptions, results, and limitations to technical teammates and learn from feedback.
  • Currently pursuing a degree in statistics, computer science, data science, machine learning, applied mathematics, econometrics, operations research, or a closely related quantitative field.

Preferred Qualifications
  • Coursework, research, or project experience using regression, time-series analysis, statistical modeling, or machine learning.
  • Exposure to Marketing Mix Modeling (MMM), marketing analytics, attribution, or other measurement problems.
  • Basic understanding of concepts such as adstock, saturation, incremental impact, ROI, or response curves.
  • Familiarity with A/B testing, causal inference, simulation, sensitivity analysis, or confidence intervals.
  • Experience with Python libraries such as pandas, NumPy, statsmodels, scikit-learn, SciPy, or similar tools.
  • Previous internship, research assistantship, academic project, or independent project involving real-world data is a plus.

NOTICE: Please be aware of fraudulent emails regarding job postings, job offers and fake checks. FocusKPI's recruiting team will strictly reach out via @focuskpi.com email domain. If you have received fraudulent emails now or in the past, please report it to https://reportfraud.ftc.gov/ .
The domain @focuskpijobs.com is fraudulent and not related to FocusKPI. Please do not not reply or communicate to anyone with @focuskpijobs.com.

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About FocusKPI

Sourced by ZipRecruiter

Industry

Computing infrastructure providers, data processing, web hosting

Company size

51 - 200 Employees

Headquarters location

Santa Clara, CA, US

Year founded

2010