[What the role is]
Are you a problem-solver who sees stories hidden within data? Join NYP's Organisational Transformation Department (OTD) to shape our future through data and AI. You will be a key member of our team, transforming raw data into actionable insights to support student success, optimize operations, and build the culture of being innovative and enterprising (I&E).[What you will be working on]
1. Build a robust data platform with Databricks
Architect and automate: Design, develop, and maintain automated data ingestion pipelines and ELT processes within our Databricks-powered platform, InnoForge.
Ensure data integrity: Take ownership of data quality by cleaning, transforming, and merging diverse datasets from multiple sources.
Govern and secure: Manage data connections, implementing access control policies, collaborating closely with IT and security teams to ensure strong data governance.
Innovate and implement: Assist with the setup, configuration, testing, and implementation of new features on the InnoForge platform.
2. Deliver strategic insights and advanced analytics
Empower decision-makers: Collaborate with various departments to create and enhance interactive Power BI dashboards that provide a clear view of institutional performance, from graduate employment outcomes to student learning analytics.
Investigate and uncover: Conduct deep-dive analysis to support strategic initiatives.
Translate complex data: Partner stakeholders to define business questions and help translate them into actionable insights.
3. Champion a data-driven culture
Enable the future: Serve as a champion to improve data literacy across NYP, empowering colleagues to use data to make more informed decisions.
Optimize processes: Work directly with department partners to identify and implement operational process improvements based on data insights.
Measure impact: Provide support to measure, analyse, and communicate OTD's engagement programs and events.
[What we are looking for]
Required skills and qualifications:
Relevant qualifications in a quantitative field such as Data Science, Statistics, Computer Science, or equivalent experience.
Experience with data visualization and dashboard development using Power BI.
Demonstrated proficiency in SQL for data querying and manipulation.
Experience with Python for data analysis and automation.
Hands-on experience with ETL processes and data pipeline development.
Strong analytical and problem-solving skills, with a meticulous eye for detail.
Nice-to-have skills:
Excellent communication skills, with the ability to tell a story with data to both technical and non-technical audiences.
Familiarity with Databricks or similar data lakehouse platforms.
Exposure to basic machine learning concepts.
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