The Business Intelligence Manager for FinTech will serve as a senior analytical resource for Product, Engineering and Finance for the FinTech business area. Their focus will be on extracting insights from product data, partnering cross functionally to optimize pricing strategies, and providing stakeholders with reporting on the health of the FinTech business. The ideal candidate is a self-starter, who is able to identify patterns in noisy data. This person will need to break down complex problems and clearly communicate their findings to all levels of stakeholders. The ideal candidate will have a track record of delivering results, complete ownership of work and outputs, finding a way to work through barriers, finding ways to work efficiently, and excellent business judgment. They should have a demonstrated ability to think analytically about the business, deliver concrete results under ambiguity, have a critical eye for detail, and have high expectations and standards.
About this roll* (Responsibilities):
- Answer business questions through independent investigation / data forensics. Identify operational inefficiencies, data quality issues, and behavioral trends.
- Build tools/dashboards to automate reporting and generate insights that will allow business leaders to quickly and accurately see how our products and processes are performing
- Report a suite of KPIs (key performance indicators) to leadership on weekly, monthly, and quarterly cadences – providing context and recommendations around opportunities and threats to the business
- Partner with key stakeholders and business leaders to provide strategic support and recommendations across various Toast departments, including: Product, Engineer, and Strategic Finance
- Identify gaps/opportunities to improve our data warehouse, synthesize requirements to the Data Engineering team, and enable stakeholders to surface new insights
Do you have the right ingredients* (Requirements)?
- 5+ years experience in Business Intelligence, Data Analytics roles and/or Bachelor’s degree in an advanced quantitative field (or equivalent experience); such as mathematics, economics/finance, computer science, or physical science
- Experience with data visualization. Can confidently choose the best visualization style for the given context; the insights from your visualizations speak for themselves
- SQL (Structured Query Language) expert
- Experience with Python (Pandas, NumPy, etc), SAS, Stata, or R
- Ability to clearly communicate findings to a range of audiences
- Ability to efficiently analyze large volumes of data, quickly draw insights, and present concise/clear recommendations of results
- Ability to work effectively in a dynamic, changing environment and to adapt while focusing on key goals and objectives
- Demonstrated problem solving with experience providing business insights and recommendations from data sets, both individually and in a group setting
Special Sauce* (Nonessential Skills/Nice to Haves):
- Background building interactive dashboards in a tool such as Looker, Tableau, Domo, SiSense, etc
- Knowledge of payments, lending and/or banking
