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Entry Level Data Monitoring Jobs (NOW HIRING)

Black Box

Data Center Cabling Technician I

Plano, TX · On-site

Our entry level Data Center Cabling Technicians perform skilled infrastructure/structured cabling ... Participate in monitoring data center environments , identifying alarms or irregular conditions ...

TWC Business Unit

Data Analyst (Statewide)

Austin, TX · On-site

$4.8K/mo

This position is in the Division of Fraud Deterrence and Compliance Monitoring (FDCM). TWC is not ... The Data Analyst I performs entry-level data analysis and data research work. Work involves ...

Ziff Davis, LLC

Data Engineer

Denver, CO · On-site

$85 - $125/hr

We're looking for an entry level Data Engineer to join the Ookla Data Engineering team and help us ... Debug queries, monitor jobs, identify bottlenecks in system performance and improve efficiency

Ookla

Data Engineer

Denver, CO

The Opportunity: We're looking for an entry level Data Engineer to join the Ookla Data Engineering ... Debug queries, monitor jobs, identify bottlenecks in system performance and improve efficiency

Ookla

Data Engineer

Denver, CO

$85K - $125K/yr

The Opportunity: We're looking for an entry level Data Engineer to join the Ookla Data Engineering ... Debug queries, monitor jobs, identify bottlenecks in system performance and improve efficiency

Ziff Davis

Data Engineer

Denver, CO · On-site +1

$85K - $125K/yr

Description Position at Ookla The Opportunity: We're looking for an entry level Data Engineer to ... Debug queries, monitor jobs, identify bottlenecks in system performance and improve efficiency

Ookla

Data Engineer

Denver, CO · On-site

$85K - $125K/yr

The Opportunity: We're looking for an entry level Data Engineer to join the Ookla Data Engineering ... Debug queries, monitor jobs, identify bottlenecks in system performance and improve efficiency

Ziff Davis

Data Engineer

Denver, CO · On-site +1

$85K - $125K/yr

Description Position at Ookla The Opportunity: We're looking for an entry level Data Engineer to ... Debug queries, monitor jobs, identify bottlenecks in system performance and improve efficiency

Ookla

Data Engineer

Denver, CO · On-site +1

$85K - $125K/yr

Description The Opportunity: We're looking for an entry level Data Engineer to join the Ookla Data ... Debug queries, monitor jobs, identify bottlenecks in system performance and improve efficiency

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Entry Level Data Monitoring information

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How much do entry level data monitoring jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for entry level data monitoring in the United States is $20.24, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $21.88 per hour, depending on experience, location, and employer.

What is an entry level data monitoring?

An entry level data monitoring job involves tracking, reviewing, and reporting data to ensure accuracy and compliance with organizational standards. Employees in this role typically use software tools to monitor data sources, identify inconsistencies or errors, and communicate findings to supervisors or other departments. These roles are essential in industries such as finance, healthcare, and IT, where data integrity is critical. No advanced experience is required, but strong attention to detail and basic computer skills are important.

What are the key skills and qualifications needed to thrive as an entry level data monitoring professional?

To excel in Entry Level Data Monitoring, you need strong analytical abilities, attention to detail, and basic knowledge of data management, often supported by a relevant associate or bachelor’s degree. Familiarity with spreadsheet software like Microsoft Excel, database systems, and data visualization tools is commonly required. Effective communication, critical thinking, and reliability are important soft skills for interpreting data trends and alerting teams to anomalies. These skills ensure accurate data tracking, timely issue identification, and support informed decision-making within organizations.

What are some common challenges faced in an entry level data monitoring position and how can new hires overcome them?

Entry level data monitoring professionals often encounter challenges such as managing large volumes of data, ensuring accuracy under tight deadlines, and quickly identifying anomalies or inconsistencies. New hires can overcome these hurdles by becoming proficient with data management tools used by their team, asking questions when unsure about data patterns, and developing strong attention to detail. Regular communication with team members and supervisors also helps in resolving ambiguities and staying aligned with project goals.

What is the difference between Entry Level Data Monitoring vs Data Analyst?

AspectEntry Level Data MonitoringData Analyst
Required CredentialsHigh school diploma or associate's; basic understanding of data toolsBachelor's degree in data, statistics, or related field; some certifications
Work EnvironmentData centers, online platforms, or office settingsOffice-based, collaborative teams, or remote
Employer & Industry UsageTech companies, healthcare, finance for routine data checksBusiness analysis, reporting, and decision-making roles

Entry Level Data Monitoring focuses on routine data checks and basic data quality tasks, often requiring minimal certifications. Data Analysts perform deeper data analysis, reporting, and insights generation, usually with a higher level of education and technical skills. Both roles are essential in data-driven industries but differ in complexity and scope.

What are the most commonly searched types of Data Monitoring jobs?

The most popular types of Data Monitoring jobs are:

What states have the most Entry Level Data Monitoring jobs?

States with the most job openings for Entry Level Data Monitoring jobs include:

Entry Level Data Monitoring jobs near you

Data Scientist - Fraud Detection

DataVisor

Mountain View, CA • On-site

Full-time

Medical, PTO

Posted 9 days ago

Key responsibilities

  • Develop and deploy machine learning models for fraud detection and risk assessment.

  • Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns in transactional data.

  • Collaborate with engineering and business teams to integrate ML models into production systems.

Job description

About DataVisor:
DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Position Overview:

We are looking for a motivated Entry-Level Data Scientist to join our Fraud Detection team. In this role, you will leverage your machine learning and data analysis skills to identify fraudulent activities, build predictive models, and uncover hidden patterns in large datasets. You will work closely with cross-functional teams to develop scalable solutions that enhance our fraud detection capabilities. This is a great opportunity to grow your skills in a fast-paced, data-driven environment while making a real impact in the fight against fraud.

Key Responsibilities:

  • Develop and deploy machine learning models for fraud detection and risk assessment.
  • Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns in transactional data.
  • Clean, preprocess, and analyze large datasets using Python and popular data science libraries (pandas, NumPy, scikit-learn, etc.).
  • Collaborate with engineering and business teams to integrate ML models into production systems.
  • Continuously monitor model performance and refine algorithms to improve accuracy.
  • Stay updated with the latest advancements in fraud detection techniques and ML/AI technologies.

Requirements

  • Master’s degree in Computer Science, Data Science, Statistics, or a related quantitative field. Ph.D. degree is a plus. 
  • Strong programming skills in Python and familiarity with data science libraries (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch is a plus).
  • Solid understanding of machine learning algorithms (supervised/unsupervised learning, anomaly detection, classification, etc.).
  • Experience with SQL and data manipulation/analysis in large datasets.
  • Strong problem-solving skills and patience for deep-dive data exploration.
  • Prior internship or project experience in fraud modeling, risk analysis, or related fields is a plus.
  • Excellent communication skills and ability to work in a collaborative environment.
Nice to have
  • Familiarity with big data tools (Spark, Hadoop, Dask).
  • Knowledge of graph-based fraud detection techniques.
  • Experience with cloud platforms (AWS, GCP, Azure).

Benefits

PTO, Stock Option, Health Benefits