Remote (Global)

Chainlink Labs is hiring a Data Scientist, Data Quality and Benchmarking

Chainlink Labs is hiring a Data Scientist for Data Quality and Benchmarking. In this role, you will build real-time pricing systems that produce high-integrity reference prices across thousands of assets. You'll design the models and detection logic that keep those prices trustworthy under stress.

What You'll Do

  • Build real-time pricing systems.
  • Model complex, adversarial markets to understand where risk originates.
  • When incidents occur, lead the data forensics (pre/post-trade analysis, benchmark vs. pool price deltas, liquidity gaps), quantify user impact, and ship fixes that measurably reduce recurrence.

What We're Looking For

  • Working knowledge of core DeFi primitives and how they generate on-chain signals.
  • Oracle literacy: how on/off-chain price feeds are constructed (CEX/DEX sourcing, outlier trimming, medians/TWAPs), and common failure modes (staleness, rubber-banding/instability, flatlining, thin-liquidity manipulation, flash-loan driven spikes).
  • On-chain data fluency: reading EVM logs/traces, ABIs and token standards (ERC-20/721/1155), identifying swaps/transfers/liquidations in event streams, and understanding subgraph/indexing patterns.
  • Blockchain fundamentals that impact alerting: block production/finality/reorgs, mempool dynamics, gas markets, and chain-specific latency characteristics that influence MTTD/MTTR and false positives.
  • Market microstructure awareness: liquidity depth, slippage, pool imbalance, funding rates/open interest (for perps), and how these drive benchmark construction and deviation alerts.

Nice to Have

  • Hands-on with Chainlink data products (Data Feeds/Mercury/Streams/CCIP) and oracle attack surfaces; prior incident response or post-mortem work on price/peg/latency events.
  • Ability to read simple smart contracts (Solidity/Rust) to validate event schemas; experience operating against major RPC providers and with indexing stacks (subgraphs, BigQuery public chains).
  • Experience designing anomaly detection for financial time series and standing up SLO-driven alerting with Prometheus/Alertmanager/Grafana/Flink + on-call tools (PagerDuty).
  • Python/SQL with web3 libraries (web3.py/ethers), ABI decoders; Dune/Flipside/Covalent/BigQuery; Kafka/stream processing. Portfolio showing dashboards/alerts for protocol health, price benchmarks vs. pool prices, and data-quality detectors (staleness/flatline/latency).

Technical Stack

  • Python, SQL, web3 libraries (web3.py/ethers), ABI decoders
  • Dune, Flipside, Covalent, BigQuery
  • Kafka, stream processing
  • Prometheus, Alertmanager, Grafana, Flink
  • Solidity, Rust

Work Mode

This role operates on a global scale.

Chainlink Labs is an equal opportunity employer. All qualified applicants will receive equal consideration for employment in compliance with applicable laws, regulations, or ordinances.

Required Skills
PythonSQLweb3.pyethers.jsABI decodersDune AnalyticsFlipside CryptoCovalentBigQueryKafkastream processingdata qualitybenchmarkingblockchain datadata pipelines PythonSQLweb3.pyethers.jsABI decodersDune AnalyticsFlipside CryptoCovalentBigQueryKafkastream processingdata qualitybenchmarkingblockchain datadata pipelines
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About company
Chainlink Labs
Chainlink is the industry-standard oracle platform bringing the capital markets onchain and powering the majority of decentralized finance (DeFi). The Chainlink stack provides the essential data, interoperability, compliance, and privacy standards needed to power advanced blockchain use cases for institutional tokenized assets, lending, payments, stablecoins, and more. Chainlink leverages a novel fee model where offchain and onchain revenue from enterprise adoption is converted to LINK tokens and stored in a strategic Chainlink Reserve.
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Job Details
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Posted 6 months ago