Learning Analytics Specialist

Waad Education; Saudi Arabia; On-site; SAR 200,000 - 300,000; Full time

Job summary

An educational organization based in Saudi Arabia seeks a Learning Analytics Specialist to drive data-informed decision-making across its schools. The role focuses on collecting, analyzing, and interpreting learning data to support school improvement efforts. Ideal candidates should hold a relevant degree and possess 3-5 years of experience in learning analytics. Proficiency in Power BI and fluency in Arabic and English are essential. Competitive benefits and a collaborative work environment are offered.

Qualifications

• 3–5 years of relevant experience in learning analytics or educational data systems.
• Proficient in essential data management tools.

Responsibilities

• Lead the collection and management of learning data across all schools.
• Analyze data to identify learning gaps and growth patterns.
• Develop reporting templates and dashboards for various stakeholders.
• Create early warning systems based on predictive analytics.
• Provide strategic data insights for planning and decision-making.
• Promote data literacy among school staff and leaders.

Skills

Data analysis

Data management

Power BI

Excel

Learning Management Systems (LMS)

Fluency in Arabic

Fluency in English

Education

Bachelor’s or Master’s in Data Science, Educational Measurement, or related field

Job description

The Learning Analytics Specialist plays a key role in enabling data‑driven decision‑making across all Waad Education Company schools. The role involves managing learning data, supporting evidence‑based planning, and ensuring alignment with standards for school improvement.

Key Responsibilities

• A. Data Collection & Management

  Lead the collection, validation, and academic, behavioral, and engagement data across all schools. Maintain a centralized data system to ensure data accuracy, accessibility, and compliance with school improvement and accreditation standards. Collaborate with school staff to build data fluency and standardize data entry procedures.

• B. Data Analysis & Interpretation

  Analyze student performance and engagement data to identify learning gaps, growth patterns, and intervention opportunities. Disaggregate data by school, grade, subject, student subgroup, and teacher to enable targeted planning and professional development.

• C. Reporting & Visualization

  Develop role‑specific reporting templates (for principals, academic leads, subject coordinators) to ensure consistent interpretation and use of data across schools. Create user‑friendly dashboards and visual reports that support learning decisions, operational KPIs, and board‑level updates. Ensure reports align with regulatory and accreditation metrics (e.g., MOE, NEASC).

• D. Predictive Analytics & Student Support

  Create early warning systems to identify students at academic or behavioral risk and enable timely interventions. Use predictive models and historical data to support long‑term planning (e.g., student retention, subject difficulty, performance bottlenecks). Collaborate with student support teams to link data insights to personalized learning and well‑being strategies.

• E. Strategic Decision Support & Planning

  Provide the CLO and Heads of School with data insights to support planning, goal‑setting, and OKR alignment. Support the design and evaluation of pilot programs or interventions by tracking impact data and making evidence‑based recommendations. Partner with the Head of Skills, Head of Academics, and School Leaders to evaluate program effectiveness (e.g., enrichment programs, new curricula).

• F. Capacity Building & Data Literacy

  Help academic coordinators and school leaders interpret and use data to drive instruction and school improvement. Promote a culture of evidence‑based decision‑making through workshops, briefings, and on‑demand support. Contribute to the development of data literacy tools and guides.

Qualifications

• Bachelor’s or Master’s in Data Science, Educational Measurement, or related field.
• 3–5 years of relevant experience in learning analytics or educational data systems.
• Proficient in Power BI, Excel, and Learning Management Systems (LMS).
• Fluency in Arabic and English.