Role overview

6+ years of demonstrated ability (Bachelor) OR 5+ years of proven experience (Masters) in a data-focused role such as product analytics, business analytics, business operations, or data science
Education in Engineering, Computer Science, Math, Economics, Statistics or equivalent experience
More than 4 years experience in modern programming languages (Matlab, Python) or statistical languages (SQL, SAS, R)
Past experience with a Product / Tech company serving large number of customers on multiple platforms
BA/BS in Mathematics, Statistics, Computer Science, Economics, Business or analytical field
SQL mastery. Write efficient and complex code in SQL
Experience in Python/R and in experimentation, A/B testing, and statistical modeling a plus
Define business metrics, including Key Performance Indicators, for financial products, in close partnership with Product Management and other leaders
Proven ability to handle large datasets, explore and use raw data feeds with excellent data visualization skills
Love of data - you just go get the data you need and turn it into an insightful story. You know how to convert data into decisions without getting stuck in paralysis by analysis
A well-organized, structured approach to problem-solving
Strong sense of ownership, accountability, and entrepreneurial spirit
Great communicator, problem-solver & confident in decision making
Independent & autonomous, while still a strong teammate
Enthusiastic, self-starting and thrives in changing, agile environments

What you'll work on

Build and lead a team of Analysts to be staffed based on highest needs across product and engineering
Work with Product and Engineering leaders to define the roadmap of these charters and create analytical projects for the team
Identify key opportunities in improving our products and platform
Extensive data analytics and SQL query writing
Interpret large amounts of complex data to formulate problem statements, concise conclusions regarding underlying risk dynamics, trends, and opportunities
Identify key risk indicators and metrics while developing and monitoring key parameters, enhance reporting, and identify new areas of analytic focus to better understand the product improvements being made
Own product data - end to end - ranging from the discovery of the business problem to eventually working with the Engineering/Product teams to execute it
Strategy design and analysis of domain-specific use-cases; Improve monitoring mechanism to alert any anomaly in business metric; and Drive multiple experiments to evaluate and quantify the hypothesis
Predictive modeling / Machine learning algorithms - using random Forest / Decision tree / Logistic regression

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