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No Experience Entry Level Data Science Jobs in Decatur, IL

Codvo.ai

Data Scientist (Dallas)

Texas, IL

... not data science jargon. Responsibilities Discovery & Baseline (Weeks 1-2) * Conduct the BMS ... Experience with HVAC, mechanical, or electrical systems is a strong advantage - someone who knows ...

AdientOne Consulting

Lab Technician |

Decatur, IL · On-site

$18.50 - $24.50/hr

... data systems. The entry level Laboratory Technician must have completed training on one aisle prior ... The Entry Level Laboratory Technician position requires no previous laboratory experience, but ...

ADM

Lab Technician (Relief Swing Shift)

Decatur, IL · On-site

$22.41/hr

... data systems. The entry level Laboratory Technician must have completed training on one aisle prior ... Entry Level Laboratory Technician position requires no previous laboratory experience but ...

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How much do no experience entry level data science jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for no experience entry level data science in Decatur, IL is $18.48, according to ZipRecruiter salary data. Most workers in this role earn between $15.62 and $20.77 per hour, depending on experience, location, and employer.

What is a no experience entry level data science job?

No Experience Entry Level Data Science jobs are positions designed for individuals who are new to the field of data science and may not have any prior professional experience. These roles typically focus on candidates with foundational knowledge of data analysis, statistics, and basic programming skills, often gained through coursework, bootcamps, or self-study. Employers for these positions generally provide training and mentorship, allowing new hires to learn practical data science skills on the job. Such positions are a great way for beginners to gain hands-on experience and start building a career in data science.

What are the key skills and qualifications needed to thrive as a no experience entry level data scientist?

To thrive as a No Experience Entry Level Data Scientist, you need a solid understanding of statistics, basic programming (often Python or R), and foundational knowledge in data analysis, typically supported by a relevant degree or coursework. Familiarity with tools like Excel, Jupyter Notebook, and introductory machine learning libraries such as scikit-learn or pandas is commonly expected. Curiosity, problem-solving skills, and a willingness to learn quickly help candidates stand out in this fast-evolving field. These abilities are crucial for analyzing data effectively, drawing meaningful insights, and adapting to new technologies and challenges in data science roles.

What are common challenges faced by individuals starting in entry-level data science roles with no prior experience?

Individuals beginning in entry-level data science positions without prior experience often face challenges such as getting up to speed with real-world datasets, learning to use industry-standard tools (like Python, SQL, or Tableau), and understanding how to translate business problems into data-driven solutions. Adapting to collaborative work environments, where projects often require teamwork with analysts, engineers, and business stakeholders, can also be a learning curve. However, most organizations provide mentorship and training opportunities to help new hires develop these skills quickly and grow within the team.

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No Experience Entry Level Data Science jobs near you
Infographic showing various No Experience Entry Level Data Science job openings in Decatur, IL as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 19% Part Time, and 4% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $38,439 per year, or $18.5 per hour.

Data Scientist (Dallas)

Codvo.ai

Texas, IL

Full-time

Re-posted 22 days ago

Job description

Data Scientist 

 

About Us: 

At Codvo, we are committed to building scalable, future-ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting-edge technology.


Role Summary 

The on-site technical presence during the pilot and Wave 1. Works directly with the customer's

maintenance team to validate alerts, tune models, and build trust in the platform's outputs.

This role requires someone who can explain machine learning predictions in maintenance

engineering language, not data science jargon.


Responsibilities 

Discovery & Baseline (Weeks 1-2)

  • Conduct the BMS protocol audit alongside the customer's controls engineer - identify available tags, data quality, polling rates, historian configuration
  • Extract and analyze the 30-day historian pull - identify operating modes, load patterns, seasonal variations, and data gaps
  • Build the baseline operating profile for each monitored equipment unit
  • Review the customer's maintenance logs - identify the 3-5 known fault events that will serve as ground truth validation
  • Map the customer's equipment taxonomy to NEIO's equipment family catalog - confirm coverage, flag gaps

Model Tuning & Validation (Weeks 3-5)

  • Monitor live anomaly scores and triage the first alerts - determine true positive vs. false positive vs. ambiguous
  • Facilitate the alert review sessions with the site maintenance lead - present alerts in context, gather feedback, document site-specific operating knowledge that affects interpretation
  • Tune the physics constraint gate to the site's operating ranges - adjust thermodynamic bounds, load-dependent thresholds, equipment-specific parameters
  • Calibrate fault classification confidence thresholds - Platt scaling, ECE measurement, reliability diagram review
  • Validate time-to-failure estimates against known maintenance history
  • Document all tuning decisions and rationale - this becomes the playbook for fleet rollout

Phase 2 (Wave 1 Sites)

  • Travel to Wave 1 sites for the 1-week discovery phase at each site
  • Conduct on-site tag mapping review with each site's controls engineer
  • Facilitate the alert review session at each Wave 1 site
  • Train the offshore Data Scientist on site-specific tuning decisions so they can handle
  • Wave 2 remotely

 

 

Expected Background 

  • 5+ years in applied data science or machine learning - predictive maintenance, anomaly detection, or industrial process optimization
  • Strong understanding of time-series analysis, classification models (XGBoost, LightGBM), and calibration techniques
  • Ability to explain model behavior to non-technical maintenance engineers - "the model flagged this because superheat is trending 3 degrees above normal for this load condition" not "the feature importance vector shows..."
  • Comfortable working on-site at a data center or industrial facility
  • Experience with HVAC, mechanical, or electrical systems is a strong advantage - someone who knows what a chiller does, what COP means, why approach temperature matters
Employment Type: FULL_TIME

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