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Remote Science Communication Jobs in Illinois (NOW HIRING)

Due to the remote nature of this role and associated employment requirements, the company is unable ... Own data science solutions from initial concept and feasibility assessment through production ...

Due to the remote nature of this role and associated employment requirements, the company is unable ... Own data science solutions from initial concept and feasibility assessment through production ...

Due to the remote nature of this role and associated employment requirements, the company is unable ... Own data science solutions from initial concept and feasibility assessment through production ...

Data Scientist

Chicago, IL · On-site +1

$90.16K - $135.24K/yr

... science team responsible for designing and delivering powerful analytical insights utilizing ... communication and presentation skills are required. This role can have a Hybrid or Remote work ...

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Remote Science Communication information

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

To thrive as a Remote Science Communicator, you need a strong background in science, excellent writing or multimedia communication skills, and at least a bachelor's degree in a relevant field. Familiarity with digital communication tools, content management systems, and social media platforms is typically required, and certifications in science communication or digital marketing can be beneficial. Exceptional soft skills include creativity, adaptability, and the ability to translate complex scientific concepts into accessible language. These skills are crucial for effectively engaging diverse audiences and ensuring accurate dissemination of scientific information in a remote environment.

What are some common challenges faced by professionals in remote science communication roles, and how can they be addressed?

One common challenge in remote science communication is ensuring clear and engaging messaging without face-to-face interaction, which can make it harder to gauge audience understanding. Collaborating across time zones and managing effective communication with scientists and stakeholders can also be complex. To address these, remote science communicators often rely on regular virtual meetings, collaborative tools, and clear documentation of project goals and feedback. Building a strong digital presence and adapting content for different online platforms are also key strategies for success in this role.

What is remote science communication?

Remote science communication involves sharing scientific information, research, and discoveries with diverse audiences using digital platforms, rather than in-person events. Professionals in this field may create content for websites, social media, podcasts, webinars, or virtual conferences, aiming to make complex scientific topics accessible and engaging. This role requires strong communication skills, science literacy, and the ability to use digital tools effectively. Remote science communicators often collaborate with researchers, educators, and media outlets from anywhere in the world.

What is the difference between Remote Science Communication vs Remote Science Writing?

AspectRemote Science CommunicationRemote Science Writing
Required CredentialsScience degrees, communication skills, possibly certifications in science communicationScience degrees, strong writing skills, possibly certifications in technical or scientific writing
Work EnvironmentVirtual, often involves multimedia, presentations, and public engagementPrimarily virtual, focused on creating written content like articles, reports, and manuals
Employer & Industry UsageResearch institutions, science media outlets, educational organizationsScientific publishers, research organizations, educational platforms
Search & Comparison IntentUnderstanding roles involving science communication and outreachLooking for scientific writing opportunities and content creation roles

Remote Science Communication focuses on conveying scientific concepts through various media and engaging audiences, while Remote Science Writing emphasizes creating written scientific content. Both roles require science backgrounds but differ in their primary output and communication methods.

What are the most commonly searched types of Science Communication jobs in Illinois? The most popular types of Science Communication jobs in Illinois are:
What are popular job titles related to Remote Science Communication jobs in Illinois? For Remote Science Communication jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Remote Science Communication jobs in Illinois look for? The top searched job categories for Remote Science Communication jobs in Illinois are:
What cities in Illinois are hiring for Remote Science Communication jobs? Cities in Illinois with the most Remote Science Communication job openings:
Infographic showing various Remote Science Communication job openings in Illinois as of May 2026, with employment types broken down into 33% Full Time, and 67% Part Time. Highlights an 67% In-person, and 33% Remote job distribution.
Sr. Data Scientist

Sr. Data Scientist

HNI Corporation

Chicago, IL • On-site, Remote

Full-time

Posted 6 days ago


HNI Corporation rating

7.7

Company rating: 7.7 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

10th of 46 rated furniture manufacturers


Job description

HNI Corporation is a global family of brands for the workplace and home dedicated to enhancing the spaces where we live, work, and gather. We pride ourselves on fostering an environment where we make a positive impact on others; upholding our beliefs in integrity, inclusion and belonging.
 
The Senior Data Scientist is a highly experienced individual contributor within the Decision Science team, responsible for solving complex, cross-functional, and high-impact business problems using advanced analytics, machine learning, and statistical modeling. This role goes beyond model development to include technical leadershipsolution design, and end-to-end ownership of data science initiatives—from problem framing and data strategy through production deployment and performance monitoring.
 
As a senior member of the team, this role helps shape HNI’s data science standards, mentors other data scientists, and partners closely with business and IT leaders to ensure data science solutions are scalable, reliable, and aligned to strategic priorities.
 
WORK AUTHORIZATION & LOCATION REQUIREMENT
 
This position is primarily remote but requires candidates to reside within the Chicagoland area and attend occasional onsite meetings as needed. Due to the remote nature of this role and associated employment requirements, the company is unable to provide employment-based visa sponsorship now or in the future. Applicants must be authorized to work in the United States without sponsorship, and candidates requiring current or future sponsorship will not be considered.
ESSENTIAL DUTIES AND REPONSIBILITIES
Advanced Analytics & Model Development
  • Lead the design, development, and deployment of advanced predictive, prescriptive, and machine learning models to support enterprise decision-making.
  • Apply advanced statistical techniques, feature engineering, and algorithm selection to complex, multi-source datasets.
  • Use SQL, Python and related tools to analyze large-scale internal and external data sources.
  • Identify patterns, trends, and drivers of business performance across manufacturing, supply chain, sales, and operations.

End-to-End Solution Ownership

  • Own data science solutions from initial concept and feasibility assessment through production deployment and ongoing optimization.
  • Define modeling approaches, validation strategies, and performance metrics to ensure business value and technical rigor.
  • Monitor deployed models for performance, drift, and stability; recommend enhancements or retraining strategies.
  • Partner with data engineering and IT teams to ensure models are production-ready and operationally supported.

Business Partnership & Communication

  • Translate complex analytical concepts and results into clear, actionable insights for business leaders and non-technical stakeholders.
  • Act as a trusted analytics advisor to cross-functional partners, influencing decisions through data-driven recommendations.
  • Support executive-level discussions by framing trade-offs, assumptions, and risks associated with analytical solutions.

Technical Leadership & Standards

  • Establish and promote best practices for model development, documentation, testing, and deployment.
  • Mentor and guide junior and mid-level data scientists, providing technical feedback and coaching.
  • Contribute to the evolution of HNI’s data science toolset, methodologies, and operating model.
  • Evaluate emerging analytics, ML, and AI techniques and recommend practical adoption.

Data Strategy & Innovation

  • Collaborate on the design of data collection strategies, analytics pipelines, and feature stores that improve modeling effectiveness.
  • Partner with analytics, BI, and data platform teams to ensure data science outputs are usable across the enterprise.
  • Support advanced use cases such as optimization, simulation, and early-stage AI initiatives.
EXPERIENCE AND REQUIRED SKILLS
  • 7+ years of progressive experience in advanced analytics, data science, or machine learning roles.
  • Master’s degree or PhD in Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative discipline.
  • Demonstrated success delivering end-to-end data science solutions in a production environment.
  • Deep hands-on expertise with SQL and Python..
  • Strong experience working in cloud-based environments (Azure preferred; AWS/GCP acceptable).
  • Solid understanding of Linux-based systems and distributed computing environments.
  • Exceptional analytical, problem-solving, and critical-thinking skills.
  • Strong communication, consulting, and stakeholder engagement capabilities.

PREFERRED QUALIFICATIONS

  • Experience supporting analytics in manufacturing, supply chain, or complex operational environments.
  • Exposure to MLOps practices, model lifecycle management, or scalable deployment frameworks.
  • Experience collaborating with data engineers, architects, and platform teams.
  • Familiarity with advanced analytics use cases such as optimization, forecasting, or AI-enabled decision support.

RELEVANT SKILLS

  • Strategic thinker with the ability to connect analytical work to business outcomes.
  • Technically curious, with a passion for continuous learning and innovation.
  • Comfortable operating with ambiguity and shaping problem definitions.
  • Collaborative mentor who elevates team capability without formal authority.
  • High standards for accuracy, reproducibility, and analytical rigor.
We look forward to hearing from you!

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