Jobs at Intropic

10-week internship developing client-facing solutions, financial research, and technical systems. Tasks include debugging Python, deploying infrastructure, building REST APIs and data pipelines, shipping production-quality code, supporting clients, testing bespoke workflows, and liaising between clients, product, and engineering to drive product enhancements.

Monitor and analyze market-moving corporate events and public company news, extract information from primary sources, validate model outputs, write research reports, communicate with clients, and improve research processes and data quality.

Build and maintain production-quality Python services and data pipelines for financial datasets, implement REST APIs, use SQL for analysis, deploy to cloud infrastructure with CI/CD, collaborate with product and research teams, and operationalise quantitative research into reproducible production workflows.

Serve as first client contact, answer and research financial market queries, collaborate with research/data teams for complex issues, manage multiple client conversations, and produce proactive written updates and research notes to help clients derive value from Intropic's data products.

10-week on-site internship focused on financial research, client-facing work, and building production technical solutions. Tasks include debugging and deploying Python code, developing REST APIs and data pipelines, maintaining production systems, supporting clients, workflow testing bespoke solutions, and liaising between clients, product, and engineering teams to drive product enhancement.

10-week on-site internship for STEM/Econ/Finance students. Work across client-facing roles, financial research, and engineering: debug Python, deploy infra changes, build REST APIs, data pipelines and Python libraries, maintain production systems, support clients, test bespoke solutions, and liaise between clients, account management, and engineering. Requires independent delivery, cross-departmental communication, and capital markets understanding.

Design, implement and operate full-stack features end-to-end: backend services and APIs in Python, frontend applications in React+TypeScript, and deploy/manage cloud-native AWS infrastructure. Maintain, monitor, and improve production systems, CI/CD pipelines, testing, and developer workflows while collaborating with product and stakeholders.

Track and analyze market-moving corporate events and public company news, extract and validate information from primary sources, check model outputs, write research reports and client notes, communicate findings to clients, and help improve research processes and data quality.

Lead cross-functional teams to build financial data products for capital markets participants, manage the business unit P&L and strategy, and report to founders. Apply ECM domain expertise (IPOs, follow-ons, block trades, convertible deals) to evaluate new-issue opportunities, allocation strategy, pricing/order-book analysis, and aftermarket liquidity. Combine product, engineering, and financial analysis skills to deliver APIs and data services for institutional clients.

10-week on-site internship combining quantitative research and engineering: build Python systems, data pipelines, APIs, and production-ready tools to analyse large financial datasets, implement and operationalise models, deploy and maintain systems (cloud, CI/CD), and deliver a meaningful project while collaborating with researchers, engineers and stakeholders.

Design, build, and maintain low-latency real-time and historical market data pipelines; ensure data integrity, availability, and performance; monitor metrics and build operational tools; collaborate with product and trading teams to align infrastructure with strategic needs; deliver well-tested, maintainable code.

Track and analyse market-moving corporate events and public company news, extract and summarise key information from primary sources, build auditable calculations and scenarios, write concise research notes, validate internal tool outputs, and improve research processes and data quality.

Design, build, and maintain performant PostgreSQL datastores, scalable data pipelines, and production-ready Python HTTP APIs. Ensure data quality, integrity, and query performance for financial datasets. Collaborate with researchers and clients to translate needs into features, using automated testing to own features from conception through deployment.