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No Experience Data Analyst Machine Learning Jobs in Chicago, IL

Qfanalytics

Machine Learning Engineer

Chicago, IL · On-site

$80 - $120/hr

They'll be working on cutting edge Quantitative Data Analysis and Machine Learning challenges. Our ... Join our team and experience the synergy that comes from working together in person, while also ...

New

Gotion, Inc.

Data Analyst

Manteno, IL

Role Summary We are looking for two Data Analyst to join our team in Fremont, CA. This is an ... Experience with implementing machine learning in industry is a plus. * Knowledge of lithium-ion ...

Gotion, Inc.

Data Analyst

Manteno, IL · On-site

Role Summary We are looking for two Data Analyst to join our team in Fremont, CA. This is an ... Experience with implementing machine learning in industry is a plus. * Knowledge of lithium-ion ...

Paylocity

Machine Learning Engineer

Schaumburg, IL · On-site

... data science, or other quantitative field, with no additional experience required. * Experience in building production-grade machine learning models and infrastructure in Python. * Strong background ...

Inspire11

Data Analyst

Chicago, IL · On-site

Hands-on experience with data visualization tools such as Power BI, Tableau, or equivalent ... Familiarity with AI and machine learning concepts and an ability to explore how GenAI (e.g ...

Inspire11

Data Analyst

Chicago, IL · On-site +1

Hands-on experience with data visualization tools such as Power BI, Tableau, or equivalent ... Familiarity with AI and machine learning concepts and an ability to explore how GenAI (e.g ...

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No Experience Data Analyst Machine Learning information

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$35K

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$140.1K

How much do no experience data analyst machine learning jobs pay per year?

As of Aug 7, 2026, the average yearly pay for no experience data analyst machine learning in Chicago, IL is $85,131.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,400.00 and $99,900.00 per year, depending on experience, location, and employer.

What are some common challenges faced by entry-level data analysts working with machine learning, and how can they overcome them?

Entry-level data analysts working with machine learning often encounter challenges such as understanding complex algorithms, cleaning and preparing raw data, and interpreting model outputs. To overcome these obstacles, it's helpful to leverage online tutorials, seek mentorship from senior team members, and actively participate in team meetings to clarify doubts. Collaborating with data scientists and software engineers can also accelerate learning and help bridge gaps in technical knowledge. Emphasizing continuous learning and practicing on real datasets can further build confidence and competence in the field.

What are the key skills and qualifications needed to thrive as a no experience data analyst machine learning?

To thrive as a No Experience Data Analyst in Machine Learning, you need foundational knowledge in statistics, data interpretation, and basic programming skills, often gained through relevant coursework or online certificates. Familiarity with tools like Python, SQL, Excel, and machine learning libraries such as scikit-learn or TensorFlow is typically expected. Strong problem-solving, attention to detail, and a willingness to learn new concepts help set candidates apart in this entry-level role. These skills are vital for accurately analyzing data, building predictive models, and supporting data-driven decision-making in a rapidly evolving field.

What is a no experience data analyst machine learning?

A No Experience Data Analyst in Machine Learning is an entry-level professional who is starting out in data analysis with a focus on machine learning concepts, but does not yet have prior work experience in the field. These analysts typically use data tools and basic machine learning techniques to clean, organize, and interpret datasets under supervision. They often learn on the job, gaining skills in data visualization, statistical analysis, and foundational machine learning algorithms. Many begin with online courses, bootcamps, or internships to build their expertise and portfolios. This role is ideal for those transitioning into tech or analytics from different backgrounds.
What are the most commonly searched types of Data Analyst Machine Learning jobs in Chicago, IL? The most popular types of Data Analyst Machine Learning jobs in Chicago, IL are:
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No Experience Data Analyst Machine Learning jobs near you

Machine Learning Engineer

Qfanalytics

Chicago, IL • On-site

$80 - $120/hr

Other

Posted 2 days ago

New

Job description

QF Analytics LLC is a fintech company that develops and supports one of the world’s fastest-growing online trading platforms with a monthly trading volume in excess of $11 billion dollars. We are expanding our team aggressively and looking ideally for individuals with trading domain knowledge, who can help develop and support a robust financial trading infrastructure.

The Machine Learning Researcher should be interested in Financial Markets, and will be directly involved in advancing the company’s Data Analysis and Machine Learning capabilities. They’ll be working on cutting edge Quantitative Data Analysis and Machine Learning challenges. Our environment is fast paced and constantly changing; the right candidate must be able to demonstrate strong communication skills, creative solutions, and results-driven behavior in time-sensitive situations.

This opportunity presents an exciting chance for individuals seeking a dynamic work environment. The successful candidate will have the option to work in a hybrid capacity, commuting to offices in Miami, Chicago, Atlanta, Toronto (Canada) or Nassau (Bahamas), fostering a collaborative and engaging atmosphere. Join our team and experience the synergy that comes from working together in person, while also enjoying the flexibility and convenience of working from home a couple days a week.

Responsibilities

Apply strong data modelling and statistical skills to develop and implement data-driven solutions.

Curate and prepare data for supervised and unsupervised machine learning projects, ensuring data quality and compatibility.

Manipulate and analyze large datasets, including numerical and categorical data, using appropriate techniques and tools.

Utilize knowledge of classical machine learning and deep learning algorithms to address specific problem domains.

Apply ML/AI tools like TensorFlow/PyTorch to build and train models for various applications.

Interface with databases to gather relevant information for analysis and modeling.

Fuse and correlate different data feeds to gain insights and enhance predictive capabilities.

Stay updated with the latest advancements in the field of machine learning and artificial intelligence, including tools, conferences, and industry blogs.

Possess a solid understanding of capital markets concepts and quantitative financial methods to effectively apply machine learning techniques in finance-related projects.

Required Qualifications

Master’s Degree in Mathematics, Engineering, Physics or related field;

Proficiency in Python;

Strong understanding of SQL for data manipulation and extraction;

Solid knowledge of probability and statistics to effectively analyze and interpret data;

Knowledge of applied mathematics, including convex optimization, quadratic programming, and partial differential equations;

Proficiency in analyzing and interpreting data, along with the ability to question it and draw meaningful conclusions;

Hands‑on approach and flexibility to apply various methods and techniques to generate actionable ideas;

Proactive, self‑motivated, and team‑oriented mindset, demonstrating strong analytical thinking;

Strong conceptualization, innovation, and problem‑solving skills;

Ability to communicate effectively through verbal and written presentations;

Preferred Qualifications

PhD in Mathematics, Engineering, Physics or related field;

4-8 years experience working in Machine Learning;

Experience with deep learning frameworks like TensorFlow or PyTorch;

Familiarity with C# and .NET framework;

Familiarity with Azure Environments; specifically Azure Data Functions;

Familiarity with Docker initialization and environment management.

What We Have To Offer

Flexible work arrangements when in office (including working from home periodically);

Competitive salaries, often better than industry, for comparable roles;

Daily premium lunch catering, and keeping the office stacked with fruits and snacks;

Arcade, foosball, snooker, pingpong, and fully equipped game room with latest generation gaming consoles on site;

Comprehensive health benefits plan that kicks in after 90 days of successful employment, including access to exclusive employee discounts;

Bonus and incentive programs.

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