They are looking for a high performing data scientist for their Quickbooks Capital business. QuickBooks Capital is a nimble and high-priority start-up within Intuit that is looking to reinvent small business borrowing and they are the team responsible for using their data to answer the most critical questions facing the Capital Product Managers. They are growing rapidly and need great people to generate analytical insights to understand their product and customers.
What does it take to thrive on their team? You need to be a top-notch problem solver and problem identifier as there are no points for an elegant solution to the wrong problem. It’s also a good idea to know the standard suite of analytical tools – SQL, R/Python, some sort of data visualization tool – but more importantly you must know how to learn tools quickly. They also often find that having a bit of a software engineering mindset is valued too – much like good software solutions, good analytical solutions are scalable and repeatable as this is what allows them to solve a problem once and go tackle the next one. Last, knowing that in most cases done is better than perfect is important – getting the current problem right to the sixth decimal place is almost always less impactful than getting to the next problem.
They are looking for team members that love new challenges, cracking tough problems and working cross-functionally. If you are looking to join a fast-paced, innovative and incredibly fun team go check out the product (quickbookscapital.com) and if you find this exciting, then we look forward to hearing from you!
- Be an analytical thought partner to the business, using data to influence the future direction of the business
- Solve product analytics problems by doing work such as developing data structures, pipelines, and data visualizations that enable them to find insights and take action by working with click data, event data, user provided data, third party data, risk data and more
- Perform analyses that inform decisions on everything from retention strategy to product experience using predictive and descriptive analytical techniques
- Communicate findings from analyses in a way that enables business leaders to make better decisions
- Partner with product analysts and engineers to understand the product roadmap and institute tracking for new features
- Ability to help design and execute product experiments through A/B testing
- Champion data-driven decision-making in your team and throughout the company, including coaching and mentoring others on best practices
- 5+ years of experience in generating and sharing insights from product data
- Fluency in data analysis, including defining KPIs, statistical and predictive modeling concepts, descriptive statistics, experimental design and A/B testing
- Exceptional SQL skills, some form of coding (Python, Scala, R etc.), and ETL/scheduling tools such as Airflow/Tidal
- Experience with data visualization tools such as Tableau etc.
- Experience working with SaaS-based subscription metrics including conversion, retention and product usage is preferred
- Entrepreneurial spirit and passionate about data
- Undergrad Degree in a Quantitative Field (Masters preferred)
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1