​This is a full-time Senior Data Analyst role at Array, a remote-first financial innovation platform providing credit, identity, and privacy monitoring tools. This position is highly technical, focusing on partnering with Engineering and Product teams to solve deep technical challenges related to data quality, code, and system reliability within the fintech space.

• ​Location: Remote (USA or Canada).
• ​Compensation Transparency: $300 per day for the 2-day paid interview. $80 per hour for the 180-day contract/probationary period. (Full-time salary not listed).
• ​Reporting: Likely reports to the CEO or Data Lead.
• ​Hiring Process Note: Includes a 2-day paid interview technical assignment and a potential 180-day contract or probationary period.
• ​Focus: Tracing issues through pipelines/code, improving data reliability, technical documentation (Jira), and accelerating analysis using AI tools.

​You Will: Debugging, Reliability, and Technical Culture

​The Senior Data Analyst is expected to be deeply curious about system mechanics and drive technical clarity and reliability across product releases.

• ​Technical Debugging: Trace issues back through data pipelines or code to uncover why something isn’t behaving as expected.
• ​System Reliability: Partner with engineers and product managers to make data and code more reliable, faster, and easier to understand.
• ​Technical Documentation: Write clear, concise Jira tickets explaining findings, fixes, and prevention methods.
• ​Culture Building: Help build a culture of technical curiosity—where asking why and testing assumptions is part of every release.
• ​AI Leverage: Instinctively use AI tools to think, build, and ship faster.
• ​Insight Generation: Develop data-driven insights that help improve user experience and drive conversion rates.

​Required Skills and Qualifications

​This role requires a unique blend of analytical rigor, coding literacy, and an entrepreneurial mindset for problem-solving.

• ​Technical Literacy:
  • ​Strong knowledge of SQL.
  • ​Familiarity with Python.
  • ​Experience digging into JSONs, logs, or API outputs to validate data flow.
  • ​Comfortable reading and reasoning about someone else’s code, identifying performance bottlenecks.
• ​Problem-Solving: The ability to turn ambiguous problems into clear next steps and a mindset that values being less wrong each time (humility and rigor).
• ​AI Mindset: A belief that AI is reshaping work, and the instinct to use it to accelerate tasks.
• ​Core Trait: A curiosity about how systems, code, and data work; a knack to pull things apart and see what’s really happening under the hood.