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Data Science Entry Level Remote Jobs in Massachusetts

FocusKPI Inc.

Data Science Intern

Boston, MA · On-site +1

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 ...

American Income Life

Entry-Level Remote Sales

Miami, FL · On-site +1

Position: Entry-Level Manager - Leadership Development Track (Remote) If you're driven, coachable ... Monitor performance data and help your team strategize for success * Organize and lead virtual ...

Fisher Organization

Entry-Level Remote Sales

Lowell, MA · Remote

Position: Entry-Level Manager - Leadership Development Track (Remote) If you're driven, coachable ... data and help your team strategize for success Organize and lead virtual training and onboarding ...

Kemper

Data Scientist

Boston, MA · On-site +1

Data Science is a driver of significant competitive advantage for Kemper and is critical to the ... Remote options are available for non-local candidate. * The range for this position is $93,300 to ...

Amgen

Data Scientist

Cambridge, MA · On-site +1

$114K - $133K/yr

Our award-winning culture is collaborative, innovative, and science based. If you have a passion ... Flexible work models, including remote and hybrid work arrangements, where possible Apply now and ...

Tempus

Data Scientist II, Outcomes Research

Boston, MA · On-site +1

$100K - $150K/yr

Advanced degree (Master's with 2+ years experience or equivalent) in data science, bioinformatics ... Additionally, for remote roles open to individuals in unincorporated Los Angeles - including remote ...

Synex Talent

Oncology Data Specialist

Northborough, MA · Remote

$120K - $150K/yr

... remote position. Based in Northborough, this role plays a crucial part in harnessing data to ... Associate's degree in Data Science, Health Informatics, or a related field * 1-3 years of ...

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Data Science Entry Level Remote information

What is a data science entry level remote job?

Data science entry level remote jobs are positions suitable for individuals who are just starting their careers in data science and prefer or require the flexibility to work from home or any location outside the traditional office setting. These roles typically involve tasks such as data cleaning, basic statistical analysis, creating simple data visualizations, and assisting with machine learning projects under supervision. Entry level data scientists often work closely with more experienced team members and use tools like Python, R, SQL, and Excel. Remote roles require good communication skills and self-motivation, as collaboration happens online. These positions are a great way to gain practical experience and develop technical skills in the field of data science.

What skills and qualifications are needed to thrive as an entry-level remote data scientist?

To thrive as an entry-level remote Data Scientist, you need a solid background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree or certification. Familiarity with tools like Jupyter Notebook, SQL databases, and machine learning libraries such as scikit-learn or TensorFlow is commonly required. Strong problem-solving abilities, communication skills, and self-motivation are crucial soft skills for remote collaboration and project management. These competencies enable effective data-driven insights, seamless teamwork, and measurable contributions in a distributed work environment.

What challenges do entry-level data scientists face when working remotely, and how can they overcome them?

Entry-level data scientists working remotely often encounter challenges such as limited access to mentorship, difficulty in collaborating on complex projects, and adjusting to asynchronous communication. To overcome these, it's important to proactively seek guidance from senior team members through regular check-ins, participate actively in team meetings and online forums, and document your work thoroughly for transparency. Leveraging collaborative tools like shared code repositories and communication platforms can also help maintain strong connections with your team and ensure project alignment.

What is the difference between Data Science Entry Level Remote vs Data Analyst Entry Level Remote?

AspectData Science Entry Level RemoteData Analyst Entry Level Remote
Required CredentialsBachelor's in CS, Statistics, or related field; some knowledge of programming and machine learningBachelor's in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentRemote, collaborative teams, often with cross-functional departmentsRemote, often working independently or with business teams
Employer & Industry UsageTech companies, finance, healthcare, e-commerceBusiness, marketing, finance, healthcare

While both roles are entry-level remote positions involving data, Data Science Entry Level Remote focuses on programming, machine learning, and predictive modeling, whereas Data Analyst Entry Level Remote emphasizes data visualization, reporting, and interpreting data for business insights. Candidates should choose based on their skills and career interests.

What are the most commonly searched types of Data Science Remote jobs in Massachusetts?

The most popular types of Data Science Remote jobs in Massachusetts are:

What are popular job titles related to Data Science Entry Level Remote jobs in Massachusetts?

For Data Science Entry Level Remote jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Data Science Entry Level Remote jobs in Massachusetts look for?

The top searched job categories for Data Science Entry Level Remote jobs in Massachusetts are:

What cities in Massachusetts are hiring for Data Science Entry Level Remote jobs?

Cities in Massachusetts with the most Data Science Entry Level Remote job openings:

Data Science Entry Level Remote jobs near you
Infographic showing various Data Science Entry Level Remote job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Data Science Intern

Boston, MA • On-site, Remote

FocusKPI Inc.
Computing Infrastructure Providers, Data Processing, Web Hosting • 51 - 200 employees
Learn more about FocusKPI Inc.external

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

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