Original listing text, shown exactly as published by the company.
Requirements for the Role
- 4 - 6 years of experience in analytics, data engineering, or data science, ideally within a high-growth tech or fintech environment
- Advanced SQL proficiency (ideally Snowflake) with the ability to write complex, highly optimized queries (CTEs, window functions) and debug performance issues
- Business strategy experience. A proven ability to partner with non-technical stakeholders, translating complex data into actionable business recommendations
- Exposure to data modeling & transformation (dbt). Hands on experience building production-grade data models, testing logic and maintaining code via version control
- Familiarity with BI tools (preferably Metabase) and experience with design and maintaining dashboards
- Highly motivated and comfortable working in a fast-paced, dynamic environment with a high degree of ambiguity.
- Bachelor’s degree in a quantitative field such as Economics, Engineering, Statistics, Mathematics, Computer Science, or related discipline.
How We Define Success
- You generate commercial impact. You don’t report the news; you make the news. You identify and execute projects that directly result in positive net income decisions (i.e. optimized marketing spend, improving credit risk models, or increasing customer LTV)
- You demonstrate the ability to self start: taking a vague business question, scoping the requirements, building the necessary data models, and delivering the final insight without needing significant guidance
- You become a trusted partner for the leaders in our business, proactively answering ‘what’s next’ rather than reacting to requests
Nice To Have, but Not Mandatory
- Experience in the fintech or banking industry.
- Proficiency in Python (pandas, numpy) for complex statistical analysis or data manipulation beyond SQL capabilities
- Specific experience with Fivetran, Heap, Snowflake, and dbt.
- Strong opinion on analytics engineering development cycle (data modeling, version control, documentation, testing & best practices)
- Familiarity with machine learning techniques and their application in business contexts.
- Experience with customer segmentation and lifecycle analysis.
Novo values diversity as a core tenet of the work we do and the businesses we serve. We are an equal opportunity employer, indiscriminate of race, religion, ethnicity, national origin, citizenship, gender, gender identity, sexual orientation, age, veteran status, disability, genetic information or any other protected characteristic.
