Head of Product
We are looking for a product leader to scale Ntropy's API by growing our foundational data enrichment product. You will work closely with our CTO and engineering team on our Transaction Enrichment product, that enables the next generation of financial services, from real-time underwriting to personal finance management and beyond.
The ideal person has previously led technical products or large-scale platforms, has regularly interacted with commercial customers and partners, has an extreme attention to detail and concisely communicates complex concepts between engineering, design, legal and customer-facing teams.
- Experience with software engineering and familiarity with financial API’s.
- 3+ years experience in product management, with demonstrated experience of successfully building and shipping products at scale.
- Excellent communication ability to both technical and non-technical audiences, and ability to lead cross-functional effort across engineering, design, and go-to-market.
- You must be capable of defining a product vision together with the CTO and translating it into actionable plans.
Over the last few decades, technological innovation has relied on democratizing some of its key ingredients: knowledge (open publishing platforms), algorithms (code repositories) and computing (cloud providers). However, the last key component, data, largely remains trapped behind barriers of regulation, privacy, schema standards and competitive risk. Enabling scalable access to data will unlock enormous value for both individual developers and companies. This has only been made possible in the last few years, through advances in manifold learning algorithms and privacy-preserving computing. See our blog for more details.
One of the most valuable kinds of data today is in the financial sector. Financial data plays a key role across many industry verticals. However, it has notoriously been locked behind regulatory barriers and a lack of format standards. Our first product is an API that makes financial transactions accessible with minimal engineering overhead to both humans and machine-learning models in a scalable and privacy-preserving way.