The ideal candidate will use their passion for big data and analytics to provide insights to the business covering a range of topics. They will be responsible for conducting both recurring and ad hoc analysis for business users.
- Member of the Business Data Analysis team to drive lending, wealth, and insurance products toward achieving company goals through data-driven strategies.
- Proactively find business opportunities using data analytics and translate complex results into clear, actionable insights for product and marketing teams.
- Develop and deliver high-impact presentations to business stakeholders covering customer segmentation, customer interest, deep post-campaign analysis, cross-selling strategies, and funnel analysis.
- Design A/B testing frameworks and propose the right success metrics to the marketing and business development teams to ensure rigorous evaluation of new initiatives.
- Own analytics for assigned products by building automated analysis workflows that explain performance changes and root causes end-to-end.
- Work closely with Data Science and MIS teams to share insights and update critical factors into analytics products and business strategy.
- Foster an open team culture that motivates and challenges members, ensuring high standards for analytical rigor and creative problem-solving.
Qualifications:
- Experiences 5+ years of professional experience in data analytics, product analytics, or a similar quantitative role.
- Strong programming skills in SQL and/or Python and highly proficient with spreadsheet-based data analytics.
- Experience analyzing data from 3rd party platforms: MMP tools (Branch, Appsflyer), Google Analytics, Mixpanel, and Facebook Insights.
- Knowledge of data visualization tools (e.g., Tableau, PowerBI, QlikView, D3, or Matplotlib).
- Solid understanding of statistics including regression, time series analysis, correlation, and clustering.
- Excellent communication, presentation, and storytelling skills.
- Creative problem-solving abilities and a curious mindset to ask the right questions.
- Education: Bachelor's or Master's degree in Mathematics, Statistics, Economics, Computer Science, or a related quantitative field.
