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Remote Science Writer information

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$13

$31

$53

How much do remote science writer jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for remote science writer in Layton, UT is $31.90, according to ZipRecruiter salary data. Most workers in this role earn between $21.20 and $46.30 per hour, depending on experience, location, and employer.

What is the difference between Remote Science Writer vs Remote Scientific Content Editor?

AspectRemote Science WriterRemote Scientific Content Editor
CredentialsBachelor's or higher in science, writing experienceSimilar credentials, with additional editing or proofreading experience
Work EnvironmentRemote, freelance or full-timeRemote, often part of a publishing or research team
Employer & IndustryResearch institutions, science publications, biotech companiesScientific journals, publishing houses, research organizations
Search & Comparison IntentWriting-focused roles, content creationEditing, quality control, content refinement

Remote Science Writers focus on creating original scientific content, while Remote Scientific Content Editors review and refine existing material. Both roles require strong scientific knowledge and writing skills, but editors emphasize editing and quality assurance. Understanding these differences helps job seekers find roles aligned with their skills and career goals.

What are the key skills and qualifications needed to thrive as a Remote Science Writer, and why are they important?

A Remote Science Writer needs strong scientific literacy, excellent writing skills, and typically a degree in a scientific discipline or journalism. Familiarity with reference management tools, content management systems, and style guides such as APA or AMA is common. Attention to detail, time management, and the ability to communicate complex ideas clearly are standout soft skills. These abilities ensure the accurate, engaging, and timely delivery of scientific information to diverse audiences in a remote work environment.

What is a remote science writer?

A remote science writer is a professional who creates articles, reports, or content about scientific topics while working from a location outside of a traditional office, often from home. Their responsibilities include researching scientific developments, interviewing experts, and translating complex scientific information into clear, accessible language for various audiences. Remote science writers may work for media outlets, research institutions, educational organizations, or as freelancers. This role requires strong writing skills, scientific literacy, and the ability to work independently while meeting deadlines.

How do Remote Science Writers typically collaborate with researchers and editors while working offsite?

Remote Science Writers often use digital communication tools such as email, video conferencing, and project management platforms to coordinate with researchers, editors, and other team members. Regular check-ins and virtual meetings help clarify scientific concepts, align on content expectations, and ensure accuracy and clarity in the writing. Writers may also participate in online editorial reviews and use collaborative document platforms to receive feedback and track revisions. This structure fosters a supportive environment despite the physical distance, enabling writers to contribute effectively to multi-disciplinary projects.
What are popular job titles related to Remote Science Writer jobs in Layton, UT? For Remote Science Writer jobs in Layton, UT, the most frequently searched job titles are:
What cities near Layton, UT are hiring for Remote Science Writer jobs? Cities near Layton, UT with the most Remote Science Writer job openings:
Remote Science Writer jobs near you
Staff Data Scientist- Pricing Science

Staff Data Scientist- Pricing Science

CSC Generation

Salt Lake City, UT • Remote

Full-time

Posted 12 days ago

Job description

CSC Generation is the AI-native holding company re-engineering omnichannel retail. We acquire iconic brands and transform them with Genesis, our operating platform combining a Data Fabric, Automation Engine, proprietary tools, and shared services to modernize operations, elevate customer experience, and expand margins. With $1B+ in revenue across 13 brands, our portfolio includes Sur La Table, Backcountry, One Kings Lane, and others that serve as real-world innovation labs.
 
Reports to: Director of Finance and Business Intelligence
Location: Remote — US or Canada
About the Role
As our Staff Data Scientist, you will design and ship production pricing systems such as demand forecasting, price elasticity modeling, dynamic pricing and the experimentation infrastructure needed to measure whether they actually work.
 
This is a hard, high-stakes problem: your models will directly influence margin and revenue decisions across a portfolio of brands operating at scale. You will own the full arc from framing ambiguous business problems as well-defined ML tasks through to monitoring models that hold up in production.
 
At six months, success looks like at least one pricing model shipped to production with measurable business impact and an experimentation framework in place that your stakeholders trust. If you have spent time building pricing systems from the ground up, not just consuming them, and you care deeply about rigorous causal inference and honest model evaluation, this role was written for you.
What You'll Do
  • Design and build production ML systems for pricing, demand forecasting, and related revenue problems
  • Frame ambiguous business problems as well-defined ML tasks with clear success criteria and measurable outcomes
  • Set the standard for model evaluation, validation, and monitoring — including knowing when CV metrics are misleading and when holdout testing is the only honest answer
  • Build robust predictive models across classification, regression, time series, and causal inference
  • Identify and prevent data leakage, overfitting, and other failure modes before they reach production
  • Design and analyze experiments to measure causal impact of pricing decisions
  • Debug models that fail in production — understand why they fail, not just that they do
  • Translate model limitations, uncertainty, and risk clearly to both technical and non-technical stakeholders
  • Partner with product, engineering, and business teams to ensure ML solutions solve real problems
Required Qualifications
  • 7+ years of applied ML / data science experience with a track record of production systems that delivered measurable business impact.
  • Deep experience in pricing, demand forecasting, or revenue optimization — you have built these models end-to-end, not just consumed them.
  • Expert-level Python and SQL.
  • Deep understanding of ML fundamentals beyond API-level usage, including model evaluation, validation, and failure mode diagnosis.
  • Strong grounding in causal inference and experimental design, including the ability to distinguish correlation from causal result.
  • Ability to work with messy, real-world data and make pragmatic tradeoffs under ambiguity.
  • Familiarity with cloud ML platforms (GCP/Vertex AI or AWS/SageMaker).
  • MS or PhD in Statistics, Computer Science, Operations Research, or a related quantitative field.
Preferred Qualifications
  • Experience in e-commerce, retail, marketplace, or pricing-intensive industries such as airlines, ride-sharing, or fintech.
Why Join
The people who do best here are builders. They take ownership, move fast, and want to see the direct impact of their work.
  • Portfolio-Level Impact: Your models will influence pricing and margin decisions across a $1B+ portfolio of brands — the output of your work is visible at the executive level from day one.
  • AI-First Skill Building: Get hands-on with production ML infrastructure, causal inference at scale, and the Genesis platform — building a modern, applied ML skill set on real retail data problems.
  • Ownership: You will own the full problem from framing through production, with the autonomy to make technical decisions and the stakeholder access to see them through.
  • Competitive Benefits (CAN): Comprehensive benefits including paid time off, RRSP match, group benefits, and employee discounts across portfolio brands.
  • Competitive Benefits (US): Comprehensive benefits including paid time off, 401(k) match, medical, dental, vision, supplemental coverage, and employee discounts across portfolio brands.
Interview Process
  1. Recruiter Screen: 30-minute call to cover your background, the role, and logistics.
  2. Hiring Manager Interview: Conversation with the Director of Finance and Business Intelligence focused on your pricing science experience, approach to ambiguous ML problems, and how you've driven production impact.
  3. Technical / Case Discussion: Deep dive into a pricing or demand forecasting problem — expect questions on model evaluation, causal inference, and production failure modes. Cross-functional stakeholders may join.
  4. Executive Interview: Final conversation with senior leadership.
  5. Reference Checks: Conducted in parallel with the final stages where possible.
  6. Offer: We move quickly for the right candidate.
For US-based candidates, this posting is intended for candidates that reside in the following states:
AZ, DE, FL, GA, IN, LA, MI, MS, MO, NV, NC, OK, PA, TN, TX, UT, WV, WI, and WY.
 
For Ontario applicants, please note that this posting is for an existing vacancy.
 
The CSC Generation family of brands provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, provincial, state or local laws. 
 
The CSC Generation family of brands is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact hrbenefits@cscshared.com.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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About CSC Generation

Sourced by ZipRecruiter

CSC Generation is a multi-brand technology platform based in Merrillville, IN, United States. The organization operates in the retail sector and utilizes technology to save retail companies from going into bankruptcy, while also offering consumers the ability to lease their purchases. Founded by serial entrepreneur, Justin Yoshimura, CSC Generation has leveraged its proprietary technology and customer database to quickly revitalize distressed retail brands. The company's mission revolves around the concepts of reinvention and innovation as it aims to redefine traditional retail and direct-to-consumer models in today's digital age. Notably, the company has, to date, acquired several brands such as DirectBuy, Killion, and most notably, Z Gallerie, growing fast within the e-commerce sector.

Company size

501 - 1,000 Employees

Headquarters location

Merrillville, IN, US

Year founded

2016

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