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Entry Level Predictive Analytics Jobs (NOW HIRING)

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Entry Level Predictive Analytics information

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How much do entry level predictive analytics jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for entry level predictive analytics in the United States is $16.03, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $16.59 per hour, depending on experience, location, and employer.

What is an entry level predictive analytics?

An entry level predictive analytics job involves using statistical methods, data analysis, and machine learning techniques to make predictions about future events or trends based on historical data. People in this role typically collect, clean, and analyze data sets, build predictive models, and help organizations make data-driven decisions. Entry level positions often require familiarity with tools like Python, R, or SQL and a foundational understanding of statistics and data science concepts. These roles are ideal for recent graduates or those new to the analytics field looking to gain hands-on experience.

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

To thrive as an Entry Level Predictive Analytics professional, you should have a solid grounding in statistics, data analysis, and a relevant bachelor's degree such as mathematics, statistics, computer science, or a related field. Familiarity with data analysis tools like Python, R, SQL, and visualization platforms such as Tableau, along with basic knowledge of machine learning algorithms, is commonly required. Strong problem-solving abilities, attention to detail, and effective communication skills help translate complex data findings into actionable insights. These skills and qualities are essential for driving accurate data-driven decision making and supporting business objectives through predictive models.

What typical projects or tasks can an entry level predictive analytics professional expect to work on during their first year?

As an Entry Level Predictive Analytics professional, you will likely work on tasks such as gathering and cleaning data, developing basic predictive models under supervision, and generating reports to communicate findings to team members. You may assist with exploratory data analysis, help automate routine analytics processes, and collaborate closely with data scientists, business analysts, and IT teams. These projects are designed to build your technical foundation, familiarize you with business data, and develop your ability to translate analytics into actionable insights.

What is the difference between Entry Level Predictive Analytics vs Data Analyst?

AspectEntry Level Predictive AnalyticsData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related field; familiarity with analytics toolsBachelor's in Data, Statistics, or related field; proficiency in Excel, SQL, and visualization tools
Work EnvironmentTech companies, finance, marketing; focus on predictive modelsVarious industries; focus on data reporting and insights
Employer & Industry UsageUsed in industries leveraging predictive modeling for decision-makingCommon across industries for data reporting and analysis

Entry Level Predictive Analytics roles focus on building models to forecast future trends, requiring knowledge of statistical modeling and machine learning. Data Analysts primarily interpret existing data to generate reports and insights. While both roles require similar educational backgrounds, predictive analytics emphasizes modeling skills, whereas data analysis centers on data interpretation and visualization.

How to get into entry level predictive analytics?

To enter an entry-level predictive analytics role, develop skills in statistics, data analysis, and programming languages like Python or R. Gaining experience through internships, online courses, or certifications in tools such as SQL and machine learning can improve your prospects and prepare you for the job market.
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Infographic showing various Entry Level Predictive Analytics job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 93% Full Time, 3% Part Time, and 3% Contract. Highlights an 78% Physical, 7% Hybrid, and 15% Remote job distribution, with an average salary of $33,341 per year, or $16 per hour.

Sustainment Data Science & Analysis Support

JSL Technologies Inc.

San Diego, CA โ€ข On-site

Full-time

Re-posted 5 days ago


Job description

Sustainment Data Science & Analysis Support
San Diego, CA
About Us:
JSL Technologies, Inc. (JSL) is a certified Small Disadvantaged Business (SDB) and Veteran-Owned government contractor delivering engineering, logistics, and program support services to the Department of Defense (DoD). Our team of more than 200 professionals is dedicated to providing practical, innovative, and cost-effective solutions that support critical missions.
Headquartered in Oxnard, California, JSL supports government customers across the nation. We foster a culture built on integrity, collaboration, and accountability, empowering our employees to perform at a high level and continuously improve the way we serve our customers.
At JSL, our people are the foundation of our success. We offer competitive compensation and a comprehensive benefits package that supports the well-being and professional growth of our team.
Job Description:
JSL Technologies is seeking an entry-level Data Scientist to support Navy engineering and sustainment programs through Python-based data analysis, automation, visualization, and analytical tool development. This position is well suited for a recent college graduate with strong Python programming skills and an interest in applying data science techniques to equipment reliability, maintenance, readiness, and sustainment challenges. Prior Navy, Reliability, Availability, Maintainability, and Cost (RAM-C), logistics, or sustainment experience is not required. The selected candidate will receive exposure to Navy systems, data sources, analytical processes, and reliability terminology while working with experienced engineering and logistics personnel at the Government facility in San Diego, California.
โ€ข Develop, maintain, and improve Python scripts used to collect, clean, organize, validate, and analyze engineering, maintenance, logistics, readiness, and operational data.
โ€ข Work with structured and unstructured datasets to identify trends, patterns, anomalies, and data-quality issues.
โ€ข Automate repetitive data-processing, reporting, and visualization activities using Python and related analytical libraries.
โ€ข Support the development of dashboards, charts, reports, and other data products used by engineering and program stakeholders.
โ€ข Apply statistical analysis, machine learning, predictive analytics, or other data-science methods under the guidance of senior technical personnel.
โ€ข Assist experienced engineers and analysts in evaluating reliability, availability, maintainability, cost, readiness, and sustainment data.
โ€ข Support senior engineers and analysts in developing and evaluating RAM-C and supportability products, including reliability models, failure analyses, repair-level analyses, sparing analyses, and readiness metrics. Prior experience with these products is not required.
โ€ข Support the preparation of technical reports, readiness summaries, recurring status reports, and presentation materials.
โ€ข Document data sources, analytical methods, assumptions, code, and results so analyses are understandable and repeatable.
โ€ข Collaborate with engineers, logisticians, maintenance personnel, program personnel, and other stakeholders to understand analytical requirements.
โ€ข Learn and use Government-provided systems and tools, which may include Advana Jupiter, JIRA, Tableau, and Navy maintenance or readiness databases.
โ€ข Become familiar with RAM-C concepts and analytical products such as Failure Modes, Effects and Criticality Analysis (FMECA), Level of Repair Analysis (LORA), Mean Time Between Failures (MTBF), Mean Time to Repair (MTTR), Mean Logistics Delay Time (MLDT), and sparing analysis through on-the-job training.
โ€ข Participate in technical meetings and design reviews and provide data-analysis support as assigned.
Requirements
Minimum Qualifications:
โ€ข Must be legally authorized to work in the United States without the need for employer sponsorship now or at any time in the future.
โ€ข Ability to obtain and maintain a U.S. Government Secret security clearance.
โ€ข Bachelor's degree in Data Science, Computer Science, Software Engineering, Computer Engineering, Mathematics, Statistics, Operations Research, Engineering, or a closely related technical discipline.
โ€ข Academic, internship, research, project, or professional experience developing software or performing data analysis using Python.
โ€ข Strong understanding of Python programming fundamentals, including data structures, functions, object-oriented programming, debugging, and code documentation.
โ€ข Experience using common Python data-analysis libraries such as pandas, NumPy, SciPy, scikit-learn, Matplotlib, or comparable libraries.
โ€ข Ability to clean, transform, analyze, and visualize data from multiple sources.
โ€ข Basic understanding of statistics, data modeling, machine learning, or predictive analytics.
โ€ข Ability to communicate analytical results clearly through written reports, visualizations, and presentations.
โ€ข Ability to learn unfamiliar engineering, reliability, logistics, and Navy terminology.
โ€ข Ability to work collaboratively with engineers, analysts, logisticians, and Government personnel.
โ€ข Ability to work on-site at the Government facility in San Diego, CA.
Preferred Qualifications:
โ€ข Internship, academic, research, or project experience involving Python-based data analysis, automation, machine learning, or predictive modeling.
โ€ข Experience working with large, incomplete, or inconsistent datasets.
โ€ข Experience using Git or another version-control platform.
โ€ข Experience with SQL, relational databases, APIs, cloud-based analytics platforms, or data visualization tools.
โ€ข Experience with Tableau, Power BI, or comparable visualization tools.
โ€ข Coursework or project experience related to reliability engineering, maintenance analytics, operations research, logistics, or equipment sustainment.
โ€ข Familiarity with Department of Defense or Navy programs is beneficial but not required.
โ€ข Familiarity with JIRA, Advana Jupiter, FMECA, LORA, MTBF, MTTR, MLDT, or availability analysis is beneficial but not required.
Security Clearance:
Applicants must have an active security clearance and/or the ability to obtain and maintain a US Government Security Clearance. Selected candidates will be subject to a government security investigation and must meet eligibility requirements to obtain a DoD Government-granted security clearance. Individuals will be subject to a background investigation to include but not limited to, criminal history, employment and education verification, drug testing, and creditworthiness.
EEO:
JSL Technologies, Inc. is an equal opportunity employer. We provide equal employment opportunities to all qualified applicants and employees without discrimination with regard to race, religion, creed, color, sex, sex stereotype, pregnancy, childbirth or related medical conditions, age, sexual orientation, gender, gender identification and expression, transgender status, transitioning employees, physical or mental disability, medical condition, genetic characteristics, genetic information, marital status, registered domestic partner status, status as military, or as a veteran or as a qualified disabled veteran, ancestry, citizenship, national origin.
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed must be representative of the knowledge, skills, minimum education, training, licensure, experience, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions. Please contact HR@jsltechinc.com if you need accommodation for the application process.
Salary Description
$65,00.00-$75,00.00 Yearly