Jobs at Intropic

Provide commercial legal support across customer and supplier agreements, negotiate and draft master agreements, data licenses, NDAs; develop AI-augmented contracting playbooks; enable sales self-service; handle complex, high-impact deals alongside the General Counsel and feed learnings back into templates and tooling.

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, 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.

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.

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.

Design, build, and maintain cloud-native backend services for index data processing. Write production-ready Python, deploy and operate services on AWS, use Infrastructure as Code, and monitor/debug systems with observability tools like Prometheus and Loki. Collaborate with product, research, and engineering teams.

Design, build, and maintain performant PostgreSQL datastores, scalable data pipelines, and production-ready Python HTTP APIs. Implement automated testing, ensure data quality, and work with researchers and clients to deliver data features for financial analysis.

Work directly with quantitative clients to translate event-driven datasets into tradeable strategies. Provide hands-on Python analysis, backtests, and reproducible examples; answer data quality and methodology questions; publish research and data notes; and liaise with product, research, and engineering teams to resolve client issues and inform priorities.

Design, build, and maintain cloud-native, scalable backend services. Write clean, tested Python (with occasional Go/Rust), operate production systems on AWS, use IaC (Terraform), containerization (Docker, Kubernetes), and observability tools (Prometheus, Loki). Collaborate with product, research, and engineering teams to define requirements and ensure reliability, security, and performance.

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.

Analyze large financial datasets, validate and develop automated models, model corporate actions and index changes, write client-facing research reports, communicate insights to clients, and source public information.