Overview
The Data Analyst collects, processes and analyses data, prepares reports and visualisations, and works with project teams to turn business requirements and data findings into practical solutions.
Key responsibilities
- Evaluate opportunities to improve Vinova's client project reporting and internal workflows using data analytics and digital tools; document the expected business benefits and feasibility of proposed solutions.
- Collaborating with internal teams to translate business requirements into technical solutions.
- Meet project stakeholders to gather and document data and reporting requirements for Vinova's client projects; define the business problem, priorities, success measures and potential analytics solutions.
- Developing and maintaining dashboards, KPIs, and reports that provide insights into business performance.
- Using statistical methods and algorithms to develop predictive models for business metrics and performance.
- Designing and implementing data models to predict business outcomes and trends.
- Identifying process inefficiencies and suggesting datadriven improvements for operational and financial optimization.
- Using statistical methods and algorithms to develop predictive models for business metrics and performance.
- Ensuring data accuracy and integrity through thorough cleaning, validation, and verification processes.
- Ensure compliance with data ethics standards by handling data responsibly, maintaining privacy, and applying ethical principles in data analysis and reporting
- Creating clear, easy-to-understand visualizations that represent complex datasets for various stakeholders
- Use stakeholder interviews, problem framing, ideation and prototype feedback to develop user-centred improvements to client reporting and analytics workflows.
- Plan and track assigned data analysis deliverables, dependencies and review milestones in Jira; report progress and risks to the Project Manager and complete tasks against agreed project timelines.
- Collaborate with cross-functional teams and stakeholders to gather data insights, share findings, and establish a strong network for ongoing data-driven project
Qualifications and skills
- Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics or a related field.
- Proficiency in SQL, Python or R, and data visualisation tools such as Power BI or Tableau.
- Knowledge of statistical analysis, data modelling, data cleaning and validation.
- Ability to communicate analytical findings and work with technical and non-technical stakeholders.