Data Analyst, Business Intelligence (Business Finance)

Responsibilities

What You'll Do:

As a Data Analyst in our Financial Performance Analysis (FPA) department, you will play a pivotal role in optimizing our financial performance. You will translate complex business challenges into data-driven insights, focusing on PnL monitoring, simulation, and strategic spending mechanics.

Key Responsibilities:

• Financial Performance Analytics & Optimization:

• Develop and maintain data pipelines and dashboards for comprehensive PnL monitoring, financial forecasting, and spending efficiency analysis.

• Conduct in-depth financial simulations and "what-if" scenario analyses to evaluate the impact of various business decisions.

• Analyze the financial performance of voucher mechanics and promotional strategies, identifying opportunities for optimization to maximize ROI and minimize waste.

• Quantify the financial impact of business initiatives and provide actionable recommendations.

• Data & Analytics Expertise:

• Query, analyze, and interpret large, complex datasets (millions to billions of rows) to uncover trends, anomalies, and insights relevant to financial performance.

• Design, implement, and maintain robust data pipelines and visualization dashboards that directly support FPA needs and strategic decision-making.

• Ensure data integrity, accuracy, and adherence to best practices in data management and governance.

• Collaboration & Business Partnership:

• Partner closely with marketing, business development, and operations teams to deeply understand their financial challenges and objectives.

• Translate business questions into clear technical tasks and analytical frameworks.

• Contribute to A/B testing design and analysis for financial campaigns and initiatives.

• Communicate complex analytical findings and recommendations clearly and effectively to non-technical stakeholders.

Requirements

• Bachelor's degree in Analytics, Data Science, Computer Science, Engineering, Actuarial Science, Finance, Economics, or a related quantitative field.
• Advanced proficiency in SQL and a strong understanding of data granularity, principles, and database structures.
• Exceptional analytical and problem-solving skills, with a keen eye for detail and accuracy.
• Outstanding communication and collaboration skills, capable of working effectively in a cross-functional environment.
• Ability to thrive independently in a fast-paced and dynamic environment.

Bonus Points If You Have:

• Proficiency in R or Python for statistical modeling, data manipulation, and visualization.
• Experience in the e-commerce or retail industry.
• Experience in financial planning.