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Data Science Research Assistant Jobs in Wayland, MA

FocusKPI Inc.

Data Science Intern

Boston, MA · Remote

Data Science Intern Statistical Modeling & Marketing Measurement Remote | Internship | Full-time | ... Previous internship, research assistantship, academic project, or independent project involving ...

FocusKPI Inc.

Data Science Intern

Boston, MA · On-site +1

Data Science Intern Statistical Modeling & Marketing Measurement Remote | Internship | Full-time | ... Previous internship, research assistantship, academic project, or independent project involving ...

Harvard University

Research Assistant

Cambridge, MA · On-site

$53/hr

We are seeking a full-time Research Assistant to assist with all study phases of functional and ... data analysis and manuscript write-up. May present scientific findings at national and ...

Harvard University

Research Assistant

Cambridge, MA

$21.25 - $29.25/hr

We are seeking a full-time Research Assistant to assist with all study phases of functional and ... data analysis and manuscript write-up. May present scientific findings at national and ...

Generalist

Research Assistant

Somerville, MA · On-site

$60 - $80/hr

... Scientist. At Generalist, we are building foundation models for robots ... These models improve through a tight feedback loop: design experiments, collect data, train or ...

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All JobsData Science Research JobsData Science Research Assistant JobsData Science Research Assistant Jobs in Wayland, MA

Data Science Research Assistant information

See Wayland, MA salary details

$9

$25

$36

How much do data science research assistant jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for data science research assistant in Wayland, MA is $25.19, according to ZipRecruiter salary data. Most workers in this role earn between $21.30 and $29.28 per hour, depending on experience, location, and employer.

What does a data science research assistant do?

A Data Science Research Assistant supports research projects by gathering, cleaning, and analyzing data using statistical and computational techniques. They assist senior researchers with designing experiments, developing models, and interpreting results. Typical tasks include data preprocessing, coding in languages like Python or R, literature reviews, and creating visualizations to summarize findings. Their work helps advance scientific knowledge and inform decision-making based on data-driven insights.

What are the key skills and qualifications needed to thrive as a data science research assistant?

To thrive as a Data Science Research Assistant, you need a strong background in statistics, machine learning, and programming (often with a degree in computer science, statistics, or related fields). Familiarity with tools such as Python, R, Jupyter Notebooks, and data visualization libraries as well as experience with version control systems like Git is typical, and coursework or certifications in data science can be beneficial. Attention to detail, problem-solving ability, and strong communication skills are essential to effectively analyze data, interpret results, and collaborate with research teams. These skills and qualities are critical for producing reliable insights, supporting research objectives, and ensuring the integrity of data-driven projects.

How does a data science research assistant typically collaborate with other team members during a research project?

Data Science Research Assistants frequently work alongside data scientists, research leads, and subject matter experts to support ongoing research. Their responsibilities often include cleaning and preprocessing data, performing exploratory analyses, and implementing models. Regular collaboration occurs through team meetings, code reviews, and sharing findings, ensuring alignment with project goals. Open communication and adaptability are essential, as priorities and datasets can shift based on project needs.

What is the difference between Data Science Research Assistant vs Data Analyst?

AspectData Science Research AssistantData Analyst
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fieldBachelor's or higher in Data Analysis, Statistics, or related field
Work EnvironmentResearch labs, academic institutions, or research-focused organizationsBusiness settings, corporate offices, or consulting firms
Employer & Industry UsageUniversities, research institutes, government agenciesCorporations, marketing firms, finance, healthcare
Common Search & ComparisonYesNo

Data Science Research Assistants typically focus on supporting research projects through data collection, analysis, and modeling in academic or research settings. Data Analysts primarily interpret data to help organizations make business decisions. While both roles require strong analytical skills and knowledge of data tools, the research assistant role emphasizes academic research and experimentation, whereas data analysts focus on business insights and reporting.

What cities near Wayland, MA are hiring for Data Science Research Assistant jobs?

Cities near Wayland, MA with the most Data Science Research Assistant job openings:

Data Science Research Assistant jobs near you
Infographic showing various Data Science Research Assistant job openings in Wayland, MA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $52,400 per year, or $25.2 per hour.

Data Science Intern

FocusKPI Inc.

Boston, MA • Remote

Other

Posted 9 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

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