We’re looking for a frontend engineer who can turn complex financial outputs into clear, interactive charts, tables, and dashboards. This role starts with internal tooling and evolves toward a production-ready, customer-facing product.
You’ll work closely with our data science and engineering teams to bridge the gap between quantitative models and usable, information-dense interfaces.
What You’ll Do
• Build reusable chart and table components from structured JSON/CSV outputs produced by our data pipeline
• Develop a dashboard interface that begins as a functional scaffold and matures into a polished, production-ready application
• Collaborate with a data scientist to define output schemas that cleanly translate computation into rendering
• Connect frontend components to REST APIs, supporting both real-time and scheduled (daily) data refreshes
• Translate static, Excel-based charts and tables into interactive, web-native visualizations
Core Requirements
• React: Strong component architecture, hooks, state management, and responsive layouts
• Node.js: Comfortable building lightweight API layers or backend-for-frontend services
• PostgreSQL: Working knowledge of relational queries, including time-series data, aggregations, and joins
• Charting Libraries: Hands-on experience with one or more of the following:
Charts.js, TradingView Charts, D3, Recharts, Highcharts, Plotly, or similar
• You should be able to look at a financial chart and know how to build it
• Financial Data Familiarity: Comfort with time-series concepts such as returns, correlations, rolling windows, and economic data
• Version Control: Git / GitHub workflow
Nice to Have
• AWS experience (S3, Lambda, CloudFront)
• Prior work on fintech dashboards, trading tools, or quantitative research platforms
• A strong preference for clean, information-dense data presentation over flashy UI
Deliverables
• An interactive dashboard surfacing model outputs through charts and tables
• A reusable React component library for common financial chart types
• A clean integration layer between Python pipeline outputs and the frontend
• Clear documentation covering components, data contracts, and deployment
Engagement Details
• Contract role: 20–30 hours per week for 8–12 weeks, with potential for extension
• Remote-friendly, with preference for some overlap with U.S. time zones
• Close collaboration with our lead data scientist, principal software engineer, and platform architect