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Data Science And Analytics Jobs in Chicago, IL (NOW HIRING)

Data Science Tutor

Chicago, IL · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Bring a strong scientific lens to every analysis by ensuring methods are not only technically sound ... Data Transformation and Feature Engineering * Work across complex, multi-source datasets spanning ...

Bring a strong scientific lens to every analysis by ensuring methods are not only technically sound ... Data Transformation and Feature Engineering * Work across complex, multi-source datasets spanning ...

As Director of Data Science , you will lead the team responsible for Numerator's consumer panel ... Experience developing production methodologies rather than exploratory analyses, and designing ...

Five years of relevant experience in data science, analytics, pricing, actuarial, or related quantitative roles. A master's degree may be considered in lieu of one to two years of experience

Leads the development and implementation of advanced analytics including customer segmentation ... Modeling/Data Science or related Bonus Points If You Have * Masters Analytics, Engineering ...

Showing results 41-60

Data Science And Analytics information

See Chicago, IL salary details

$38.7K

$126.5K

$202.6K

How much do data science and analytics jobs pay per year?

As of Aug 23, 2026, the average yearly pay for data science and analytics in Chicago, IL is $126,538.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $140,200.00 per year, depending on experience, location, and employer.

What is data science and analytics?

Data Science and Analytics refer to the fields that focus on extracting meaningful insights from large and complex data sets. Data Science combines statistics, computer science, and domain knowledge to analyze data, build predictive models, and support data-driven decision-making. Analytics, which is a core part of data science, involves examining data to discover trends, patterns, and correlations that can help organizations solve problems or improve processes. Professionals in these fields use tools such as Python, R, SQL, and machine learning algorithms to analyze data and communicate findings to stakeholders.

What are some common challenges faced by data science and analytics professionals when working with cross-functional teams?

Data science and analytics professionals often collaborate with colleagues from diverse backgrounds such as engineering, marketing, and business operations. One common challenge is translating complex analytical findings into actionable insights that non-technical stakeholders can easily understand. Additionally, aligning project objectives and timelines across teams can require strong communication and project management skills. Overcoming these challenges is essential for ensuring that data-driven solutions are effectively implemented and contribute to organizational goals.

What are the key skills and qualifications needed to thrive as a data science and analytics professional, and why are they important?

To thrive in Data Science and Analytics, you need strong skills in statistics, data manipulation, and programming, typically backed by a degree in computer science, mathematics, or a related field. Proficiency with tools like Python, R, SQL, and data visualization platforms such as Tableau, along with knowledge of machine learning frameworks, is highly valued. Strong problem-solving ability, critical thinking, and effective communication skills help translate complex data findings into actionable business insights. These skills are crucial for turning raw data into strategic decisions that drive organizational success.

What is the difference between Data Science And Analytics vs Data Analysis?

AspectData Science And AnalyticsData Analysis
Required SkillsStatistical modeling, programming, machine learningData cleaning, descriptive statistics, visualization
Work EnvironmentCross-functional teams, R&D, predictive modelingBusiness reporting, dashboards, ad hoc analysis
Tools & TechnologiesPython, R, SQL, Hadoop, SparkExcel, SQL, Tableau, Power BI
Industry UsageTech, finance, healthcare, marketingRetail, finance, healthcare, operations

Data Science And Analytics involves advanced techniques like machine learning and predictive modeling, often requiring programming skills. Data Analysis focuses on interpreting existing data through descriptive statistics and visualization for decision-making. Both roles are essential but differ in complexity and scope.

What can I do with data science and analytics?

Data science and analytics professionals analyze large datasets to extract insights, support decision-making, and improve business processes. They use tools like Python, R, and SQL, and often work in environments that require strong statistical and programming skills. These roles can lead to careers in industries such as finance, healthcare, marketing, and technology, with opportunities for advancement and specialization.

What jobs can I get with a data science and analytics degree?

A degree in data science and analytics can lead to roles such as data analyst, data scientist, business intelligence analyst, machine learning engineer, and data engineer. These positions typically require skills in programming languages like Python or R, data visualization tools, and statistical analysis, often with certifications or experience in big data platforms and SQL. Job responsibilities include interpreting complex data, building predictive models, and supporting data-driven decision-making.

What cities near Chicago, IL are hiring for Data Science And Analytics jobs?

Cities near Chicago, IL with the most Data Science And Analytics job openings:

Infographic showing various Data Science And Analytics job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $126,538 per year, or $60.8 per hour.

Data Science Tutor

Varsity Tutors

Chicago, IL • Remote

$18 - $40/hr

Part-time

Re-posted 21 days ago


Varsity Tutors rating

5.9

Company rating: 5.9 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

11th of 24 rated private schools and tutoring


Job description

About the Job
The Varsity Tutors Live Learning Platform has thousands of students looking for online Data Science tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the flexibility to set your own schedule, earn competitive rates, and make a real impact on students' academic success and understanding. All from the comfort of your home.
Why Join Our Platform?
  • Earn incrementally higher pay for each session with the same student, reaching up to $40/hour.
  • Get paid up to twice per week, ensuring fast and reliable compensation for the tutoring sessions you conduct and invoice.
  • Set your own hours and tutor as much as you'd like.
  • Tutor remotely using our purpose-built Live Learning Platform. No commuting required.
  • Get matched with students best-suited to your teaching style and expertise.
  • Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson generation, and engagement features, helping you save prep time and focus on impactful teaching.
  • We handle the logistics—you just invoice for your tutoring sessions, and we take care of payments.

What We Look For In a Data Science Tutor
  • Advanced Subject Mastery: Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data-driven insights. Ability to explain probability distributions, regression analysis, A/B testing, and data pipeline design while preparing students for data science roles, analytics careers, and graduate programs.
  • Conceptual Teaching & Problem-Solving: Skilled at teaching the full data science workflow from question formulation through insight communication. Guides students through data cleaning with Pandas, exploratory analysis with visualization libraries, building predictive models, conducting statistical tests, and creating compelling data presentations. Emphasizes translating business questions into analytical frameworks and connects data science to product management, marketing analytics, and healthcare informatics.
  • Curriculum Awareness & Adaptive Instruction: Familiar with data science curricula and bootcamp programs, and common challenges such as data cleaning complexity, selecting appropriate statistical tests, and communicating technical findings to non-technical stakeholders. Adapts instruction using Jupyter notebooks, real-world data sets, and end-to-end project workflows to support students from introductory data literacy through advanced analytics and machine learning implementation.
  • Effective Teaching Methods: Ability to identify concepts students commonly struggle with, explain material using multiple approaches, and adapt instruction to meet individual learning needs and styles.
  • Strong communication skills and a friendly, engaging teaching style.
  • Ability to adapt to different learning styles and student needs.

Ways To Connect With Students
  • 1-on-1 Online Tutoring - Provide personalized instruction to individual students.
  • Instant Tutoring - Accept on-demand tutoring requests whenever you're available.

About Varsity Tutors And 1-on-1 Online Tutoring
Our mission is to transform the way people learn by leveraging advanced technology, AI, and the latest in learning science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students receive customized instruction that helps them achieve their learning goals. Our platform is designed to match students with the right tutors, fostering better outcomes and a passion for learning.
Please note: Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New Hampshire, North Dakota, Vermont, West Virginia or Puerto Rico.

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