Work Location : Sydney, New South Wales, Australia
Work Style : Hybrid with 2 days in the office per week.

EXPERIENCE OVERVIEW

• Data Analyst Experience: 2+ years in data analytics
• Experience researching, developing and validating predictive models.
• Ability to create compelling visualizations and communicate complex topics effectively using Tableau, Excel, and other visualization tools.
• Python Proficiency: Solid experience in Python for data processing tasks, cleaning and conducting analyses
• SQL and Database Management: Competent in performing SQL queries for effective data extraction, manipulation, and analysis
• Generative AI: Foundational understanding of generative AI concepts, with the ability or interest to apply these technologies to improve data quality, research and validation.Professional fluency in English is essential
  At Pearson we ‘add life to a lifetime of learning’ so everyone can realise the life they imagine. We do this by creating vibrant and enriching learning experiences designed for real-life impact.
  Pearson is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

WHO WE ARE:

At Pearson, our purpose is simple: to help people realize the life they imagine through learning. We believe that every learning opportunity is a chance for a personal breakthrough. We are the world’s lifelong learning company. For us, learning isn’t just what we do. It’s who we are. To learn more: We are Pearson.
Pearson is an Affirmative Action and Equal Opportunity Employer and a member of E-Verify. We want a team that represents a variety of backgrounds, perspectives and skills. The more inclusive we are, the better our work will be. All employment decisions are based on qualifications, merit and business need. All qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, age, national origin, protected veteran status, disability status or any other group protected by law. We strive for a workforce that reflects the diversity of our communities.
If you are an individual with a disability and are unable or limited in your ability to use or access our career site as a result of your disability, you may request reasonable accommodations by emailing TalentExperienceGlobalTeam@grp.pearson.com.
Note that the information you provide will stay confidential and will be stored securely. It will not be seen by those involved in making decisions as part of the recruitment process.
Job: TECHNOLOGY
Organization: Workforce Skills
Schedule: FULL_TIME
Workplace Type: Hybrid
Req ID: 18143

As a Data Analyst in the Data and AI team, you will have the opportunity to collaborate closely with the Data Science team, focusing on data modelling, data quality, visualization, and insights development. This role is centred on using data and research to understand and evaluate the impact of emerging technologies on the workforce. In this role, you will be expected to support the preparation and delivery of analytical solutions, ensuring data integrity and effective communication of findings to drive team objectives.

• Research new technologies and trends in their adoption and disruption of work and industries.
• Support the preparation and delivery of insights through the creation of clear and interactive data visualizations and dashboards using tools such as Tableau or Power BI to effectively communicate complex insights and trends.
• Ensure data accuracy and reliability through benchmarking, quality checks, documenting methodologies, and translating complex technical findings into accessible insights for both technical and non-technical stakeholders.
• Assist in developing, validating, and refining predictive models related to workforce impacts, providing critical data inputs and exploratory analyses to validate assumptions and outputs
• Clean, preprocess, and transform large and complex datasets using Python and SQL, ensuring data quality and consistency.
• Collaborate with data scientists, product managers, and customer teams to identify key research questions, provide actionable data visualizations, and deliver insights.