DATA ANALYST

Vinova Pte. Ltd.; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

Vinova Pte. Ltd.

is seeking a Data Analyst to collect, process and analyse data, prepare reports and visualisations, and work with project teams to turn business requirements and data findings into practical solutions. The role involves collaborating with internal teams to translate requirements into technical solutions, developing dashboards and KPIs, and applying statistical methods to predict business outcomes while ensuring data quality and ethical handling of information for diverse

Qualifications

• Bachelor’s degree in data-related field.
• Proficiency in SQL, Python or R, and data visualization tools.
• Knowledge of statistical analysis, data modelling, cleaning and validation.
• Ability to communicate analytical findings to stakeholders.

Responsibilities

• Evaluate opportunities to improve client reporting and internal workflows using data analytics and digital tools.
• Collaborate with internal teams to translate business requirements into technical solutions.
• Meet stakeholders to gather and document data/reporting requirements and determine success measures.
• Develop and maintain dashboards, KPIs, and reports to provide business insights.
• Apply statistical methods and algorithms to develop predictive models for business metrics.
• Design and implement data models to predict outcomes and trends.
• Identify process inefficiencies and suggest data-driven improvements for optimization.
• Ensure data accuracy and integrity through cleaning, validation and verification.

Skills

Analytical thinking

Communication

Education

Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics or related field

Tools

SQL

Python

R

Power BI

Tableau

Job description

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.