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Entry Level Data Modeling Jobs in California (NOW HIRING)

... modeling and directed acyclic graphs (DAGs) for efficient data organization and processing ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

... modeling and directed acyclic graphs (DAGs) for efficient data organization and processing ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

... modeling and directed acyclic graphs (DAGs) for efficient data organization and processing ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

... modeling and directed acyclic graphs (DAGs) for efficient data organization and processing ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

... modeling and directed acyclic graphs (DAGs) for efficient data organization and processing ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Associate Data Scientist

Burbank, CA · On-site

$62K - $63K/yr

We are seeking an Associate Data Scientist for this entry-level role. You will work to support the ... Key Projects: • Leverage 1st / 2nd / 3rd party data to build global models that predict user ...

Associate Data Scientist

Burbank, CA

$62K - $63K/yr

We are seeking an Associate Data Scientist for this entry-level role. You will work to support the ... Build models to predict content viewership and identify content traits that resonate most with each ...

... 2-3 entry-level and mid-level systems analysts, apply independent, advanced technical and ... Java, ETL, PeopleSoft, Business Systems Analysis, Software Automation Test Suite, Data Modeling ...

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Showing results 1-20

Entry Level Data Modeling information

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

AspectEntry Level Data ModelingData Analyst
Required CredentialsBachelor's in CS, IS, or related; basic understanding of databasesBachelor's in Statistics, Math, or related; proficiency in data tools
Work EnvironmentDesigning data structures, collaborating with DBAs and developersAnalyzing data sets, creating reports, working with business teams
Industry UsageUsed in database design, data warehousing, and system developmentApplied in business intelligence, reporting, and data-driven decision making

Entry Level Data Modeling focuses on designing and structuring data systems, while Data Analysts interpret data to provide insights. Both roles require foundational data knowledge but differ in their primary tasks and focus areas within the data ecosystem.

What are the key skills and qualifications needed to thrive as an Entry Level Data Modeler, and why are they important?

To thrive as an Entry Level Data Modeler, you need a solid understanding of database concepts, data structures, and basic SQL, often supported by a degree in computer science or a related field. Familiarity with data modeling tools such as ER/Studio, Microsoft Visio, or IBM InfoSphere Data Architect, and knowledge of relational database management systems (RDBMS) are typically required. Strong analytical thinking, attention to detail, and effective communication help you clarify requirements and present technical information to stakeholders. These skills and qualities ensure that data models are accurate, scalable, and aligned with business needs, supporting successful data-driven projects.

Is 40 too late for data science?

Entry level data modeling roles are accessible at any age, including at 40, especially if you develop relevant skills such as SQL, data visualization, and understanding of data structures. Many professionals transition into data science or modeling careers later in life by gaining certifications or completing relevant training programs.

What is entry level data modeling?

Entry level data modeling involves creating and organizing data structures, such as diagrams and databases, to represent and manage information within an organization. Professionals in this role typically use tools to define how data is stored, accessed, and related, ensuring it supports business needs. Entry-level data modelers work closely with senior analysts and IT teams to learn best practices and standards. This position is ideal for those with foundational knowledge in databases, analytical thinking, and an interest in data-driven decision making.

How to start with data modelling?

Entry level data modeling involves understanding database concepts, learning data normalization, and practicing with tools like ER diagrams and SQL. Gaining familiarity with data management principles and obtaining certifications such as Microsoft Certified: Data Analyst Associate can also help build foundational skills.

Will AI replace data modelers?

AI is unlikely to fully replace data modelers, as their role involves designing and understanding complex data structures that require domain knowledge and critical thinking. AI tools can assist with automating routine tasks and data analysis, but human expertise remains essential for creating effective data models and ensuring data quality. Entry-level data modelers should focus on developing skills in data architecture, modeling tools, and understanding business requirements to stay valuable in the evolving field.

Can I get into data analytics with no experience?

Entry level data modeling roles often require some understanding of data structures, databases, and basic analytics tools like Excel or SQL. While prior experience is not always mandatory, gaining relevant skills through online courses, certifications, or hands-on practice can improve your chances of entering data analytics or data modeling positions.

How does an entry-level data modeler typically collaborate with other teams during a project?

As an entry-level data modeler, you will often work closely with business analysts, software engineers, and database administrators to translate business requirements into effective data structures. Collaboration often involves participating in meetings to gather requirements, reviewing data needs, and ensuring your models align with both business goals and technical constraints. You may also assist in refining models based on feedback and help maintain clear documentation for future reference. This teamwork not only improves your technical skills but also helps you understand the broader context of data-driven decision-making within the organization.
What are the most commonly searched types of Data Modeling jobs in California? The most popular types of Data Modeling jobs in California are:
Sustainment Data Science & Analysis Support

Sustainment Data Science & Analysis Support

JSL Technologies Incorporated

San Diego, CA

$65K - $75K/yr

Other

Posted 5 days ago


Job description

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.

Develop, maintain, and improve Python scripts used to collect, clean, organize, validate, and analyze engineering, maintenance, logistics, readiness, and operational data.

Work with structured and unstructured datasets to identify trends, patterns, anomalies, and data-quality issues.

Automate repetitive data-processing, reporting, and visualization activities using Python and related analytical libraries.

Support the development of dashboards, charts, reports, and other data products used by engineering and program stakeholders.

Apply statistical analysis, machine learning, predictive analytics, or other data-science methods under the guidance of senior technical personnel.

Assist experienced engineers and analysts in evaluating reliability, availability, maintainability, cost, readiness, and sustainment data.

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.

Support the preparation of technical reports, readiness summaries, recurring status reports, and presentation materials.

Document data sources, analytical methods, assumptions, code, and results so analyses are understandable and repeatable.

Collaborate with engineers, logisticians, maintenance personnel, program personnel, and other stakeholders to understand analytical requirements.

Learn and use Government-provided systems and tools, which may include Advana Jupiter, JIRA, Tableau, and Navy maintenance or readiness databases.

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.

Participate in technical meetings and design reviews and provide data-analysis support as assigned.

Requirements

  .  

Minimum Qualifications:


Must be legally authorized to work in the United States without the need for employer sponsorship now or at any time in the future.

Ability to obtain and maintain a U.S. Government Secret security clearance.

Bachelor's degree in Data Science, Computer Science, Software Engineering, Computer Engineering, Mathematics, Statistics, Operations Research, Engineering, or a closely related technical discipline.

Academic, internship, research, project, or professional experience developing software or performing data analysis using Python.

Strong understanding of Python programming fundamentals, including data structures, functions, object-oriented programming, debugging, and code documentation.

Experience using common Python data-analysis libraries such as pandas, NumPy, SciPy, scikit-learn, Matplotlib, or comparable libraries.

Ability to clean, transform, analyze, and visualize data from multiple sources.

Basic understanding of statistics, data modeling, machine learning, or predictive analytics.

Ability to communicate analytical results clearly through written reports, visualizations, and presentations.

Ability to learn unfamiliar engineering, reliability, logistics, and Navy terminology.

Ability to work collaboratively with engineers, analysts, logisticians, and Government personnel.

Ability to work on-site at the Government facility in San Diego, CA.


Preferred Qualifications:


Internship, academic, research, or project experience involving Python-based data analysis, automation, machine learning, or predictive modeling.

Experience working with large, incomplete, or inconsistent datasets.

Experience using Git or another version-control platform.

Experience with SQL, relational databases, APIs, cloud-based analytics platforms, or data visualization tools.

Experience with Tableau, Power BI, or comparable visualization tools.

Coursework or project experience related to reliability engineering, maintenance analytics, operations research, logistics, or equipment sustainment.

Familiarity with Department of Defense or Navy programs is beneficial but not required.

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.