Job description
Nova Credit | Remote (US, Canada) We're building a unified platform for credit and financial data to power financial inclusion globally. Our mission is to unlock economic opportunities for consumers historically excluded from traditional credit systems by transforming diverse data into actionable risk insights. We are YC company backed by investors from Canapi Ventures, Kleiner Perkins, General Catalyst, and Index Ventures -> Hiring software engineers from Senior to Staff, Product, and Design roles. -> Tech stack: Node.js, React, TypeScript, Python, PostgreSQL, AWS You'll work on enterprise-grade APIs, data integrations, advanced analytics, and seamless user experiences. We're looking for engineers who thrive in fast-paced environments and want to make a meaningful impact on financial inclusion. Apply at https://job-boards.greenhouse.io/novacredit and mention HN.
✍️ Tailored application (cached — grounded in your resume)
70 / 100 honest fit
Strong overlap on the backend half of Nova Credit's stack: four-plus years at Medtronic building Python backend services, REST APIs, and AWS-based data processing (Lambda, S3, DynamoDB), plus Jenkins CI/CD and automation frameworks — directly relevant to enterprise-grade APIs and data integrations. He also ships and operates full-stack Flask/Python products end-to-end on his own infrastructure, so the 'own it from API to deployment' expectation is proven, not aspirational. The honest gap is the front half of the stack: no professional Node.js, TypeScript, or React experience, and no fintech or credit-data domain background — he'd be learning the language and the domain on the job while contributing immediately on Python, AWS, data pipelines, and reliability.
Tailored resume highlights
- Built and optimized backend services and REST APIs for connected medical devices at Medtronic, ensuring reliable data delivery and system performance across embedded and cloud components.
- Implemented AWS-based solutions (Lambda, S3, DynamoDB) supporting scalable data processing and monitoring — the same cloud primitives behind high-volume data integration and analytics pipelines.
- Designed and shipped production Flask/Python full-stack web applications end-to-end on self-hosted Linux infrastructure — gunicorn, hardened endpoints, per-IP rate limiting, automated cron data pipelines, and self-healing watchdogs serving real organic traffic.
- Developed Python automation frameworks integrated into Jenkins CI/CD, enabling reproducible deployments and cutting manual regression effort by 40% while increasing test reliability.
- Led root-cause analysis of complex field-found issues, reproducing rare defects in-house and driving resolution across multiple teams — deep debugging of cross-team, cross-system data flows.
"Why this company?" (draft — personalize before sending)
Nova Credit's core problem is data integration: pulling messy credit data from many sources and turning it into risk decisions people's financial lives depend on. I've spent four years at Medtronic building backend services and validation pipelines for connected medical devices, where a bad data path isn't a bug report — it's a patient safety issue. That instinct, prove the pipeline is correct before you ship it, maps directly onto credit decisioning. I also build and operate my own production Flask/AWS services end-to-end, so owning enterprise-grade APIs from schema to deployment is how I already work, not a stretch.
Cover letter (review before sending)
Dear Nova Credit Team,
I'm applying for your Senior/Staff Software Engineer role. For the past four years at Medtronic I've built backend services, REST APIs, and validation pipelines for connected medical devices, using Python and AWS (Lambda, S3, DynamoDB) to move device telemetry reliably into cloud data processing. In regulated medical-device software, correctness and reliability aren't features — they're requirements. That's the same standard credit and risk data deserves.
Your stack overlaps with most of my daily work: Python, AWS, SQL, and REST microservices, plus Jenkins CI/CD and Python automation frameworks I've used to make deployments reproducible and cut manual regression effort by 40%. I've also led root-cause analysis on rare field-found defects across multiple teams — the kind of debugging data-integration work demands when one upstream source starts behaving differently.
Outside work, I design, ship, and operate production Flask/Python applications on my own infrastructure — hardened endpoints, rate limiting, cron data pipelines, self-healing watchdogs — using Claude Code as a core part of my workflow. I'd bring that end-to-end ownership and speed to Nova Credit.
Daniel Maynard
ATS keywords you have but should add
Full-stack developmentFlaskData integration / data pipelinesRelational databases (SQL)API authentication and access controlProduction monitoring and observabilityLinux server operations (gunicorn)Rate limiting / endpoint hardeningRemote / distributed collaboration
Everything is grounded strictly in your resume — review before you submit. Nothing is auto-sent.