Job Description

Job Advert Summary

At Boxer, we're continually looking to connect with talented analytical professionals who are passionate about using data to drive business decisions. Whether your experience lies in Rewards & HR Analytics or in the Commercial/Business Analytics space, we'd like to hear from you.

Minimum Requirements

A relevant bachelor's degree in Statistics, Analytics, Economics, Business Intelligence, IT, or related fields. 3 to 5 years of professional experience in data analytics, which may include HR/Rewards data, commercial/retail analytics, or supply chain data. Advanced proficiency in Excel (including complex formulas, pivot tables, and macros/VBA). Experience with data visualization tools such as Power BI or similar platforms for dashboard and report development. Strong analytical and statistical skills, with the ability to interpret complex data and translate it into actionable business insights. Effective communication skills to present data findings clearly to non-technical stakeholders. A proactive approach to problem-solving, attention to detail, and ability to work under pressure. Additional desirable qualifications or certifications in business analysis or data analytics may be advantageous but not always essential.

Duties and Responsibilities

Collect, clean, and analyze large datasets from multiple sources including HR, rewards, commercial, and supply chain data. Develop, maintain, and enhance dashboards and reports using Excel, Power BI, or similar tools for effective data visualization. Translate complex data into clear, actionable insights to support business planning, budgeting, forecasting, and decision-making. Collaborate with cross-functional teams such as marketing, merchandising, supply chain, and HR to interpret data and provide insights. Conduct market, competitor, and trend analysis to identify growth opportunities and inform strategy. Perform root cause analysis on data anomalies or performance issues and recommend solutions. Design and implement A/B tests or modeling to evaluate business initiatives and forecast trends. Present findings and recommendations clearly to non-technical stakeholders and senior management. Ensure data accuracy, consistency, and integrity through validation and monitoring processes. Support integration of new data sources and analytical tools, and keep up with industry trends and best practices. * Mentor and support junior analysts when required.