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Binance Accelerator Program - Applied Data Scientist
Binance
Remote, AUS
Internship
Entry
Remote
Discovered 2 weeks ago
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Free
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Role Overview
You'll work directly on the AI systems powering Binance AI Products and next-generation agentic trading features — alongside the full-time algorithm team, on real production challenges.
You own deliverables, run experiments, and ship code that matters. You build components of AI systems (agents, pipelines, evaluation tools), debug real systems, and work with engineers to ship features that reach users.
This is not a "watch and learn" program. You are expected to build, contribute, and ship.
Key Skills for This Role
PythonClaude CodeCursorGitHub Copilot WorkspaceMCP
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About the Role
You'll work directly on the AI systems powering Binance AI Products and next-generation agentic trading features — alongside the full-time algorithm team, on real production challenges.
You own deliverables, run experiments, and ship code that matters. You build components of AI systems (agents, pipelines, evaluation tools), debug real systems, and work with engineers to ship features that reach users.
This is not a "watch and learn" program. You are expected to build, contribute, and ship.
Responsibilities
- Contribute to the design and development of LLM-powered pipelines for agentic trading — including reasoning agent components, tool-use frameworks via MCP, and automated workflow execution across crypto markets.
- Build and evaluate prompt engineering strategies, test-time scaling approaches, and retrieval architectures for crypto-native data sources — on-chain data, market feeds, news, and sentiment signals.
- Design and run model evaluation experiments — defining quality metrics for agent reasoning in financial contexts, executing benchmarks, and synthesizing results into actionable findings.
- Analyze agent performance characteristics in live trading scenarios — covering decision accuracy, latency, reliability, and adversarial robustness.
- Apply AI-native development practices using agentic coding tools as a standard part of the engineering workflow — writing and executing Python code for strategy logic, data pipelines, and agent evaluation.
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