Academic Data Analyst

At Pearson, we’re committed to a world that’s always learning and to our talented team who makes it all possible. We are bold thinkers and standout innovators who push the boundaries of technology. We create seeds of learning that become the catalyst for the world’s innovations. Within the Pearson Virtual Schools (PVS) division we have reimagined K-12 education through our virtual school and curriculum offerings. Our schools, Connections Academy and Pearson Online Academy, provide a best-in-class online learning environment for K-12 students to acquire the skills and confidence they need to adapt and thrive in a changing world. We also support school districts with curriculum, teachers, and technology as they make the shift to online. The COVID-19 pandemic introduced significant disruption and transformation to the K-12 learning market. And as a result, our category has seen explosive growth and our business has experienced enormous increases in awareness and enrollments. This presents an incredible opportunity for our team to chart a ground-breaking path through this shifting environment to achieve continued success.

SUMMARY

The Academic Data Analyst is a member of the Academic Impact department, a department within Pearson Virtual School (PVS). The Academic Data Analyst is responsible for collecting, analyzing, and interpreting student performance data to support decision-making processes, professional development topics, and instructional tools to drive academic excellence. The role involves collaborating with Academic Impact, Research and Efficacy, and Customer Success Partners staff to provide insights that contribute to the improvement of academic programs, student outcomes, and organization effectiveness.

REQUIRED SKILLS, EXPERIENCE, AND COMPETENCIES

• Degree in a relevant field with proven experience in the area of data analysis.
• Proven experience in data analysis and interpretation, preferably in an academic or educational setting.
• Working knowledge of Microsoft Excel including formulae and data management.
• Knowledge of PowerBI or other data visualization tools and/or SQL would be a plus.
• Excellent communication skills to convey complex technical information to non-technical stakeholders.
• Familiarity with educational systems and structures.
• Attention to detail and a commitment to data accuracy and integrity.
• Works well in a matrix - Models collaboration, solves problems with peers, builds trust and support.
• Takes personal responsibility – Can be relied on to complete tasks timely and well, demonstrates “ownership” regardless of the outcome, proactive in exploring and exploiting new opportunities.
  Compensation at Pearson is influenced by a wide array of factors including but not limited to skill set, level of experience, and specific location. As required by the Colorado, California, Washington State, New York State and New York City laws, the pay range for this position is as follows:
  The minimum full-time salary range is between $60,000 - $70,000.
  This position is eligible to participate in an annual incentive program, and information on benefits offered is here.

Data Collection:

• Gather, compile, and organize Academic Data from various sources, including student records, assessment results, published data from state Department of Education or other similar organization’s web sites, surveys, and other relevant datasets.
• Develop and maintain data collection systems and databases to ensure accuracy and accessibility of information.
• Identify ways to improve efficiency in the data collection process.

Data Analysis:

• Utilize statistical methods and data analysis tools to extract meaningful patterns, trends, and correlations from Academic Datasets.
• Perform exploratory data analysis to identify areas for improvement and opportunities for academic enhancement.

Reporting:

• Generate regular and ad-hoc reports for Academic Impact Teams ,other internal PVS partners, and Connections Academy schools.
• Present findings and insights in a clear and understandable manner to facilitate informed decision-making.
• Generate data reports on the annual key results of academic outcomes.

Predictive Modelling:

• Partner with Research and Efficacy Team to identify and learn of models to forecast academic trends, student performance, and other relevant indicators.
• Collaborate with stakeholders to identify key performance indicators and metrics for predictive analysis.

Quality Assurance:

• Ensure data integrity and accuracy by conducting regular data validation and cleaning procedures.
• Implement and maintain data quality standards to uphold the reliability of academic information.

Compliance and Privacy:

• Stay informed about relevant data protection regulations and ensure compliance with privacy standards when handling Academic Data.
• Implement and uphold ethical standards in data analysis and reporting.