Data Analyst, Product Growth-Spruce

About the Role

Key Responsibilities

• Collaborate on problem statements - Work with stakeholders across product, marketing, and research to craft problem statements to inform your roadmap of analyses.
• Design, complete and report out on analyses - Complete self-led work to deliver on problem statements by designing, completing and sharing results from analyses.
• Make recommendations based on findings - Emphasize the 'so what' in your analyses and make recommendations or propose experiments to help affirm your conclusions.
• Work with multiple data sources to find ways to answer complex questions - Leverage data from multiple sources including external analyses and reports, marketing technology databases, administrative databases, and technical logs, to find ways to answer complex questions.
• Monitor performance of campaigns and features - Work with marketing and product partners to identify new campaigns and feature launches and monitor their performance against their goals.
• Master primary data sources and deploy your curiosity to identify great customer stories - Learn the detail of regular data sources and begin to actively investigate opportunities to improve outcomes, or pockets of over performance that could be replicated.
• Advise on data collection processes - Reflect on gaps in available data and advise on future data collection practices.
• Prioritize short and long term requests - Work with stakeholders to ensure that short and longer term requests and analyses can be appropriately prioritized.

Requirements

• Bachelor's in Computer Science, Data Science, Information Technology, or a related field OR equivalent experience.
• 3+ years of experience in Data Science building models, constructing analyses and reporting out findings.
• Experience in Financial services.
• Proficiency in SQL and Python, familiarity with Tableau and/or PowerBI visualization tools.
• Knowledge of a variety of machine learning techniques (logistic regression, KNN, gradient boosting, random forest, SVM, Naive Bayes, etc.) and their real-world advantages/drawbacks.
• Comfort working in multiple data environments and leveraging multiple sources to answer a complex question.
• Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment.

Nice to Have

• Experience growth hacking within a fintech or other engagement context.
• Experience running research and analyses in multiple contexts.
• Analytical position oriented towards growth - acquisition, engagement, delivery mechanisms, partnerships to figure out how to grow the business.
• Masters degree in Computer Science, Data Science, Information Technology, or a related field OR equivalent experience.

Qualifications

• Bachelor's degree or equivalent experience in relevant field.
• 3+ years of experience in data analysis, modeling, and reporting.
• Experience in financial services.

Benefits & Perks

• Competitive compensation and benefits to support your health and well-being.
• Participation in incentive compensation or short-term incentive plans.
• Medical and prescription drug coverage.
• H&R Block Retirement Savings Plan (401(k) Plan).
• Employee Assistance Program.
• Virtual fitness center programs.
• Associate discount program.
• Automatic enrollment in Business Travel Accident Insurance.
• Associate Tax Prep benefit.