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Remote Data Science Jobs in Chicago, IL (NOW HIRING)

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Applied Science Team The Applied Science team operates at the core of Relativity's AI development.

Bachelor's degree in a quantitative field (e.g., CS, Statistics, Physics, Engineering) and 1+ years of professional experience in Data Science or Data Engineering.2. Proficiency in SQL: Ability to ...

Bachelor's degree or higher - Quantitative field such as Computing Science, Statistics, Mathematics ... Working hours are flexible and remote work is encouraged. We are an equal opportunity employer and ...

With offices in Chicago, Miami, and around the world through the power of remote work, we are a ... Use advanced data analytics to understand consumer risk behavior trends, their impact on the ...

Data Scientist

Chicago, IL · On-site +1

$90K - $130K/yr

With offices in Chicago, Miami, and around the world through the power of remote work, we are a ... Use advanced data analytics to understand consumer risk behavior trends, their impact on the ...

... remote global workforce. We are seeking a dynamic and experienced DS/AI Tech Partner (a Data Science Growth Leader) to join our team. This role will co-own business development and growth initiatives ...

... remote global workforce. We are seeking a dynamic and experienced DS/AI Tech Partner (a Data Science Growth Leader) to join our team. This role will co-own business development and growth initiatives ...

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Showing results 1-20

Remote Data Science information

See Chicago, IL salary details

$24.1K

$107.3K

$204.8K

How much do remote data science jobs pay per year?

As of Jun 16, 2026, the average yearly pay for remote data science in Chicago, IL is $107,302.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,426.00 and $148,830.00 per year, depending on experience, location, and employer.

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

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

Can a data scientist work fully remote?

Yes, many data scientists work fully remote, especially in companies that prioritize flexible work arrangements. Remote data science roles often require strong communication skills, proficiency with collaboration tools, and the ability to work independently on projects using programming languages like Python or R. However, some positions may require occasional in-person meetings or on-site presence depending on company policies.

Is 40 too late for data science?

Age is not a barrier to entering data science, and many professionals start or transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Will AI replace data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not eliminate the need for human expertise in interpreting results, designing models, and making strategic decisions. Data scientists will continue to be essential for developing complex algorithms, understanding business context, and ensuring ethical use of AI tools. Skills in programming, statistical analysis, and machine learning remain critical for the profession's evolving landscape.

What Are the Qualifications to Get a Remote Data Science Job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

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

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables, optimize models, and prioritize tasks for efficiency.
What are the most commonly searched types of Data Science jobs in Chicago, IL? The most popular types of Data Science jobs in Chicago, IL are:
What job categories do people searching Remote Data Science jobs in Chicago, IL look for? The top searched job categories for Remote Data Science jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Remote Data Science jobs? Cities near Chicago, IL with the most Remote Data Science job openings:
Infographic showing various Remote Data Science job openings in Chicago, IL as of June 2026, with employment types broken down into 2% As Needed, 73% Full Time, 21% Part Time, 2% Contract, and 2% Nights. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $107,302 per year, or $51.6 per hour.
Senior Data Scientist - GenAI (Retail)

Senior Data Scientist - GenAI (Retail)

Tiger Analytics Inc.

Chicago, IL • Remote

Full-time

Posted 20 days ago


Job description

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

We are seeking a highly skilled and experienced Senior Data Scientist with strong expertise in GenAI modelling. The ideal candidate will have a proven track record of designing, developing, and deploying scalable GenAI solutions, while leading projects and mentoring teams. This role requires deep technical expertise, hands-on coding experience, and the ability to collaborate closely with clients and stakeholders to translate business needs into robust analytical solutions.

Responsibilities:

  • Work on the latest applications of data science to solve business problems
  • Work directly with client stakeholders to translate business problems into high level analytics solution designs
  • Present analytic solutions to business audiences highlighting robustness of the solution and how it could help generate business value
  • Develop end-to-end solutions based on in-depth understanding of business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably
  • Design and develop machine learning and Generative AI solutions using Databricks and Azure AI services.
  • Build LLM-powered applications and orchestrate workflows using LangGraph
  • Develop agentic AI workflows for automation, insights generation, and decision support
  • Implement Document Intelligence solutions for extracting insights from unstructured data
  • Participate in discussions with team members to select and apply relevant analytic techniques and create actionable business insights
  • Responsible for making presentations to senior management, communicating results to business teams, and develop plans to help operationalize analytic solution

Requirements

  • 8 - 10 years of professional work experience with at least 5 years in Data Science
  • Proficiency in Python and SQL
  • Practical exposure to Retail , supply chain domain problems such as logistics, distribution networks, or demand planning.
  • Experience with MLflow and model lifecycle management
  • Generative AI Knowledge: Solid understanding of latest-generation AI concepts including LLMs, prompt engineering, retrieval-augmented generation (RAG), and other contemporary generative AI applications
  • Experience with sequential algorithms (e.g., LSTM, RNN, transformer, etc.)
  • Experience with Bedrock, JumpStart, HuggingFace
  • Experience evaluating ethical implications of AI and controlling for them (e.g., red-teaming)
  • Expertise in supervised learning and unsupervised learning along with experience in deep learning and transfer learning
  • Experience in generative algorithms (e.g., GAN, VAE, etc.) as well as pre-trained models (e.g., LLaMa, SAM, etc.)
  • Ability to work with IT and Data Engineering teams to help embed analytic outputs in business processes
  • Experience building end-to-end ML pipelines in production
  • Familiarity with CI/CD pipelines, monitoring, and model governance
  • Ability to design scalable and reliable AI systems
  • Bachelor's in Business Analytics or equivalent work experience.

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.