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Data Science Writer Jobs in Boston, MA (NOW HIRING)

CarGurus

Senior Data Scientist

Boston, MA

Design A/B tests of the Data Science team's models and analyze their results * Communicate solutions to stakeholders through written documentation, demos and presentations, and data visualizations

Jobtailor

Principal Data Scientist

Acton, MA · On-site

* Define and evolve analytical methodologies, standards, and best practices across the Data Science ... Exceptional written and verbal communication skills, including the ability to explain complex ...

The Hollister Group

Data Scientist - NYC

Boston, MA · On-site

$100 - $200/hr

Experience with machine learning or adjacent fields (natural language processing, random forests, linear regression, predictive modeling, and entry-level data science concepts) * Experience writing ...

YO AI Labs

AI Data Scientist Expert - Remote

Boston, MA · Remote

$100 - $200/hr

Job Title: AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job ... Technical & Report Writing * Content Review & Editing * Data Annotation * Data Interpretation

YO AI Labs

AI Data Scientist Expert - Remote

Boston, MA · Remote

$100 - $200/hr

Job Title: AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job ... Technical & Report Writing * Content Review & Editing * Data Annotation * Data Interpretation

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All JobsData Science Writer JobsData Science Writer Jobs in Boston, MA

Data Science Writer information

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How much do data science writer jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for data science writer in Boston, MA is $26.39, according to ZipRecruiter salary data. Most workers in this role earn between $20.10 and $30.29 per hour, depending on experience, location, and employer.

What is a data science writer?

A Data Science Writer is a professional who specializes in creating content related to data science topics, such as machine learning, artificial intelligence, data analytics, and statistical modeling. They translate complex technical concepts into clear, accessible articles, tutorials, blog posts, or documentation for audiences ranging from beginners to experts. Data Science Writers often work for tech companies, educational platforms, or media outlets, helping to educate and inform readers about current trends and developments in the data science field.

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

To thrive as a Data Science Writer, you need a strong understanding of data science concepts, analytics, and statistics, supported by experience in technical writing or journalism. Familiarity with tools such as Python, R, Jupyter Notebooks, and visualization platforms, as well as SEO practices, is typically required. Exceptional communication, storytelling, and the ability to simplify complex topics are critical soft skills in this role. These skills ensure that technical information is accurately conveyed to diverse audiences, enhancing understanding and engagement.

How does a data science writer typically collaborate with subject matter experts and data professionals?

Data Science Writers often work closely with data scientists, analysts, and engineers to translate complex technical concepts into accessible content for a wider audience. Collaboration usually involves interviewing experts, reviewing technical documentation, and attending team meetings to stay updated on project developments. This process ensures accuracy and clarity in the content, while also helping writers understand emerging trends and tools in data science. Effective communication skills and a willingness to learn from technical colleagues are essential for building strong working relationships.

What is the difference between Data Science Writer vs Data Analyst?

AspectData Science WriterData Analyst
Required CredentialsBachelor's or higher in Data Science, Communications, or related fields; strong writing skillsBachelor's in Statistics, Data Science, or related fields; proficiency in data tools
Work EnvironmentContent creation teams, tech companies, research organizationsBusiness, finance, healthcare, and other industries analyzing data
Employer & Industry UsageTech firms, media outlets, educational platformsCorporations, consulting firms, government agencies
Common Search & ComparisonYesNo

The main difference between a Data Science Writer and a Data Analyst lies in their focus. Data Science Writers primarily create content explaining data concepts, insights, and research findings, requiring strong writing and communication skills. Data Analysts, on the other hand, analyze data sets to generate reports and support decision-making. While both roles involve working with data, their core responsibilities and skill sets differ significantly.

Are data science writers in demand?

Data science writers are in increasing demand as organizations seek clear communication of complex data insights. They often require skills in data visualization, technical writing, and familiarity with tools like Python or R, making their expertise valuable across industries such as technology, finance, and healthcare.
Infographic showing various Data Science Writer job openings in Boston, MA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, and 5% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $54,884 per year, or $26.4 per hour.

Senior Scientist I, Data Science

Cambridge, MA • On-site

Sail Biomedicines
See more jobs at Sail Biomedicinesexternal

$130K - $170K/yr

Full-time

Re-posted 12 days ago

Job description

The Position
Join our team and drive the future of programmable eRNATM therapeutics and In Vivo CAR-T therapies- where AI-driven biology, targeted delivery systems and next-generation immunotherapy converge to redefine what's possible for patients. As a key member of the Sail Biomedicines Data Science team, the Senior Scientist I will operate at the interface of platform and program, applying data-driven approaches to champion broad platform efforts and hands-on analysis of preclinical datasets to transform the treatment landscape for autoimmune diseases, and beyond.
The ideal candidate will combine strong biological insight with quantitative rigor, applying data-driven approaches to extract actionable understanding from complex preclinical and platform datasets while helping establish scalable computational foundations for future discovery efforts. In addition to supporting in vivo CAR immunology programs, this role will contribute to emerging capabilities in systems modeling, computational protein design, molecular modeling, and AI/ML-enabled therapeutic engineering.
Partnering closely with experimental scientists, you will spearhead efforts to translate platform and program data into actionable understanding of biology, enabling rapid iteration across our therapeutic learning cycle.
Responsibilities
  • Perform in-depth analysis of preclinical and platform datasets, including immunophenotyping, functional assays, and multi-omics data to support both therapeutic programs and platform development
  • Integrate and interpret data across studies and contexts to generate biological insights that inform CAR activity, persistence, immune dynamics and platform-level understanding of our therapeutics
  • Collaborate closely with immunology and platform teams to inform experimental design and interpret results
  • Work resourcefully with internal/external datasets to contextualize findings and strengthen conclusions
  • Apply statistical and systems modeling to develop deeper understanding of product and platform attributes and performance.
  • Apply and promote best practices in data structuring, annotation, and metadata usage to enable reliable, scalable and reusable downstream analysis across programs and platform efforts
  • Develop and maintain reproducible analysis workflows, with clear documentation and version control (Git) and contribute to a well-organized data environment by following FAIR-aligned practices in day-to-day work
  • Communicate findings clearly with collaborators through visualizations, presentations, and written summaries

Qualifications
Required:
  • Ph.D. in Computational Biology, Bioinformatics, Systems Biology, Biophysics or related field
  • 3+ years of experience analyzing multifaceted biological datasets in biotech, pharma, or academia
  • Firsthand experience working in CAR-T or RNA therapeutics.
  • Demonstrated experience applying modeling (statistical, system) to biological data.
  • Strong expertise in high-dimensional data analysis (e.g., RNA-seq, single-cell, in vivo studies) with the ability to transform raw data to refined downstream biological interpretations
  • Proficiency in Python and/or R, with strong data analysis and visualization skills and a firm grasp of modern statistics (mixed models, Bayesian methods, etc.)
  • Experience building reproducible and well-documented analysis workflows (Nextflow, Snakemake) and applying sound data organization and metadata practices
  • Demonstrated ability to champion cross-functional efforts in close collaboration with experimental scientists, taking ownership and driving insights even in areas outside your core subject matter expertise

Preferred:
  • Computational design of Antibody/VHH/scFv/CAR proteins
  • Experience in immunology, cell therapy, or CAR biology, particularly in vivo systems
  • Experience integrating complex datasets and cross-study meta-analysis
  • Exposure to cloud-based or collaborative data environments
  • Track record of impactful scientific contributions (publications or program support)

About Sail Biomedicines
Sail Biomedicines is building a new class of fully programmable medicines by integrating circular RNA (eRNAâ„¢), targeted nanoparticle delivery, and advanced computational approaches. Our platform enables the systematic design and optimization of therapies, unlocking new possibilities across immunology and beyond.
Salary Range: $130,000 - $170,000
Sail Biomedicines is an Equal Opportunity Employer. Sail does not discriminate based on race, religion, color, sex, gender identity, sexual orientation, age, national origin, veteran status, or any other status protected under federal, state, or local law.

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