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Entry Level Learning Analytics Jobs (NOW HIRING)

Precise - Int

Entry Level Financial Analyst

Boston, MA · On-site

$51K - $56K/yr

... of Entry Level Financial Analysts for our rapidly growing Boston office. We are seeking an ... learning capabilities and fast-learner • Complete honesty combined with a strong team player ...

Precise - Int

Entry Level Financial Analyst

New York, NY · On-site

$55K - $60K/yr

... Entry Level Financial Analysts for our rapidly growing New York office. We are seeking an ... learning capabilities and fast-learner • Complete honesty combined with a strong team player ...

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Entry Level Learning Analytics information

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$60.5K

$123.8K

$175K

How much do entry level learning analytics jobs pay per year?

As of Jun 19, 2026, the average yearly pay for entry level learning analytics in the United States is $123,849.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $153,500.00 per year, depending on experience, location, and employer.

What are the 4 types of learning analytics?

The four types of learning analytics are descriptive, diagnostic, predictive, and prescriptive analytics. Descriptive analytics analyze past data to understand what has happened, while diagnostic analytics explore why it happened. Predictive analytics forecast future outcomes, and prescriptive analytics recommend actions to improve learning outcomes, making them useful for entry-level learning analytics roles that involve data interpretation and decision-making.

How can I get into data analytics with no experience?

Entry level learning analytics roles typically require foundational skills in data analysis, such as proficiency in Excel, SQL, or data visualization tools like Tableau. Gaining relevant knowledge through online courses, certifications, or internships can help build your skills and improve your chances of entering the field without prior experience.

What are entry level learning analytics jobs?

Entry level learning analytics jobs are positions designed for individuals who are new to the field of learning analytics. These roles typically involve collecting, analyzing, and interpreting data related to educational programs or training initiatives. Entry-level professionals may assist in generating reports, supporting research, and using data to improve learning outcomes. They often work under the guidance of more experienced analysts and are expected to be familiar with basic data analysis tools and concepts.

Is 40 too late for data science?

Entry Level Learning Analytics roles often value skills and relevant training over age, and many professionals transition into data science later in their careers. Gaining proficiency in programming languages like Python or R, along with understanding data visualization tools, can help you enter the field regardless of age. Continuous learning and certifications can also improve your chances of starting a career in data science at any age.

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

AspectEntry Level Learning AnalyticsData Analyst
Required CredentialsBachelor's in Education, Data Science, or related field; familiarity with learning management systemsBachelor's in Statistics, Mathematics, or related field; proficiency in data analysis tools
Work EnvironmentEducational institutions, e-learning platforms, corporate training programsVarious industries including finance, healthcare, marketing, and technology
Employer & Industry UsagePrimarily in education and e-learning sectorsAcross multiple industries requiring data-driven decision making

Entry Level Learning Analytics focuses on analyzing educational data to improve learning outcomes, often within educational or e-learning settings. In contrast, Data Analysts work across diverse industries to interpret data for strategic insights. While both roles require analytical skills and familiarity with data tools, Entry Level Learning Analytics emphasizes understanding educational contexts and learning management systems, making it more specialized in the education sector.

What are the key skills and qualifications needed to thrive as an Entry Level Learning Analytics professional, and why are they important?

To thrive as an Entry Level Learning Analytics professional, you need a basic understanding of data analysis, statistics, and educational measurement, typically supported by a relevant degree in education, statistics, or a related field. Familiarity with data visualization tools (like Tableau or Power BI), learning management systems (LMS), and spreadsheet software such as Excel is commonly required. Strong attention to detail, problem-solving abilities, and effective communication skills help you interpret data and collaborate with educators or organizational stakeholders. These skills are crucial for transforming raw educational data into actionable insights that enhance learning outcomes and drive informed decision-making.

What types of projects do entry-level learning analytics professionals typically work on, and how do they collaborate with instructional designers or educators?

Entry-level learning analytics professionals often support projects such as analyzing student engagement data, reporting on learning outcomes, and identifying trends in course performance. They regularly collaborate with instructional designers and educators by providing data-driven insights that inform curriculum adjustments and teaching strategies. This teamwork helps ensure that educational interventions are both effective and tailored to learner needs, offering entry-level professionals valuable experience in cross-functional communication and practical data application.

Is AI replacing data analysts?

AI is transforming the role of entry level learning analytics professionals by automating routine data processing and analysis tasks, allowing analysts to focus on interpretation and strategic insights. While AI tools can handle large datasets efficiently, human expertise remains essential for contextual understanding, decision-making, and developing complex models. Entry level analysts should develop skills in data visualization, statistical analysis, and AI tools to stay relevant in the evolving field.
More about Entry Level Learning Analytics jobs
What cities are hiring for Entry Level Learning Analytics jobs? Cities with the most Entry Level Learning Analytics job openings:
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Entry Level Learning Analytics jobs near you
Infographic showing various Entry Level Learning Analytics job openings in the United States as of June 2026, with employment types broken down into 1% Locum Tenens, 1% As Needed, 68% Full Time, 28% Part Time, 1% Temporary, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $123,849 per year, or $59.5 per hour.
Entry Level Machine Learning Engineer

Entry Level Machine Learning Engineer

SynergisticIT

Santa Fe, NM

Other

Posted 13 days ago

Job description

Synergisticit Job Opportunities

Since 2010 SynergisticIT has helped jobseekers get employed in the tech job market by providing candidates the requisite skills, experience, and technical competence to outperform at interviews and at clients. The tech job market has been affected by massive layoffs and since 2021 there have been more than 600,000 tech layoffs. The job market is hyper competitive. For 1 position 500-1000 candidates or more are applying and laid off job seekers are also competing for entry-level job positions.

We at Synergisticit understand the problem of the mismatch between employer's requirements and employee skills and that's why since 2010 we have helped 1000's of candidates get jobs at technology clients like apple, google, Paypal, western union, client, visa, walmart lab s etc to name a few. We are continuously looking for entry-level software programmers, Java full stack developers, Python/Java developers, data analysts/data scientists, data engineers, machine learning engineers for full-time positions with clients. Who should apply? Recent computer science/engineering/mathematics/statistics or science graduates or people looking to switch careers or who have had gaps in employment and looking to make their careers in the tech industry.

We need data science/machine learning/data analyst and Java full stack candidates. Preferred skills for Java/full stack/devops positions include a bachelors degree or masters degree in computer science, computer engineering, electrical engineering, information systems, IT knowledge of core Java, javascript, C++ or software programming. Spring boot, microservices, Docker, Jenkins, Github, Kubernates and REST API's experience. For data science/data analyst/AI/machine learning positions preferred skills include an associate or bachelors degree or masters degree in computer science, computer engineering, electrical engineering, information systems, IT, statistics, mathematics or having good logical aptitude knowledge of statistics, gen AI, LLM, Sagemaker, Python, computer vision, data visualization tools. Candidates lacking technical skills can research our other programs which can assist in landing a job.

If you get emails from our job placement team and are not interested please email them or ask them to take you off their distribution list and make you unavailable as they share the same database with the client servicing team who only connect with candidates who are matching client requirements. No phone calls please. Shortlisted candidates would be reached out. No third party or agency candidates or c2c candidates.

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