Data Scientist, Data Quality and Benchmarking

Chainlink Labs

11d • Remote

About The Position

We are looking for a data scientist who understands financial markets to build real-time pricing systems that produce high-integrity references prices across thousands of assets. As a member of this team, you’ll design the models and detection logic that keep those prices trustworthy under stress.

Requirements

• 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 Haves

• 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).

Responsibilities

• You’ll build real-time pricing systems.
• You’ll model complex, adversarial markets to understand where risk originates.
• When incidents occur, you’ll 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 This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 501-1,000 employees