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Junior Data Analyst
Posted on March 11, 2025
- Auckland City, New Zealand
- No Salary information.
- Full Time
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About the Role:
Support data analysis tasks that are both ad-hoc /as-needed to support better data-driven business and product decisions
Scope is initially around AI/ML risk products, then for SLG/Mobile (data gaps) then larger P&L
Must work closely with stakeholders across multiple time zones (need person to be flexible)
What you'll do:
- Produce key metrics, dashboards, and reports to support PM asks (AI/ML initiatives, tech partnerships etc.)
- Present data findings and insights to internal stakeholders, translating complex data into actionable recommendations.
- Develop and maintain interactive dashboards for real-time analytics and reporting.
- Collaborate with cross-functional teams in UK, NZ, India and US time zones, ensuring timely updates and support for all teams.
- Write, optimize, and troubleshoot SQL queries to access, manage, and analyze data within Snowflake or other relational databases.
- Assist in machine learning projects by preparing data and evaluating models, applying metrics like precision, recall, and accuracy.
- Build and maintain a comprehensive data dictionary to standardize and improve data usage across the organization.
- Support data quality initiatives by troubleshooting and validating data integrity in reports and dashboards.
What you'll bring:
- Education: Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field, or equivalent work experience.
- Some Proficiency in SQL for data querying and analysis.
- Familiarity with relational database concepts and data structures.
- Strong understanding of statistical fundamentals and measures.
- Knowledge of data warehousing principles and ETL processes.
- Experience with data visualization tools, preferably Tableau.
- Experience with data warehouse tools, preferably Snowflake.
Preferred Qualifications:
- Basic knowledge of Python for data manipulation and automation
- Prior exposure to machine learning workflows or data preparation for modeling.
- Foundational knowledge of machine learning concepts and metrics, such as precision, recall, and accuracy
- Ability to communicate effectively with technical and non-technical team members.
- Flexibility to work across multiple time zones (UK, US, India, NZ).
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