🕒 2 days ago
Collect, validate and analyse investment governance data, monitor key controls and triggers, and prepare reliable dashboards and reporting for management, Investment Committees and Board forums.
Member of Technical Staff (Search Quality Analyst)
📅 Sep 2
Data AnalysisSearch QualitySQLPython
📜 Description
- Find and diagnose quality issues in the search pipeline.
- Design metrics to track and measure search quality.
- Build model-training datasets, including LLM-as-a-judge labeling pipelines.
- Improve search snippet quality and page-selection algorithms for indexing.
- Design and analyze A/B experiments to validate improvements.
🛠️ Requirements
- 4+ years of experience as a data analyst or in a related role
- Strong coding skills — expected to write production-grade code at a mid-level backend engineer level
- Proficiency with SQL and Python
- Designing metrics from scratch (not just analyzing existing A/B experiments)
- Building labeling pipelines using LLM-as-a-judge
- Training ML models that shipped to production with measurable metric improvements
- Designing evals with known ground truth (e.g. SimpleQA, BrowseComp) or driving meaningful improvements on such evals
- Experience working on search-related products
Full job description
Perplexity is looking for an experienced analyst to help us build and improve our core search technologies. You'll work at the intersection of data analysis and engineering - designing metrics, building data pipelines, and improving the quality of our search and answer systems.
This role is hybrid in Belgrade, London or Berlin.
Responsibilities
Find and diagnose quality issues in our search pipeline
Design metrics from scratch to track and measure search quality
Build datasets for model training, including LLM-as-a-judge labeling pipelines
Improve search snippet quality and page selection algorithms for indexing
Design and analyze A/B experiments to validate improvements
Qualifications
4+ years of experience as a data analyst or in a related role
Strong coding skills — expected to write production-grade code at a mid-level backend engineer level
Proficiency with SQL and Python
Demonstrated hands-on experience with at least one of the following:
Designing metrics from scratch (not just analyzing existing A/B experiments)
Building labeling pipelines using LLM-as-a-judge
Training ML models that shipped to production with measurable metric improvements
Designing evals with known ground truth (e.g. SimpleQA, BrowseComp) or driving meaningful improvements on such evals
Nice to have
Experience working on search-related products
Knowledge of statistics and A/B experiment design
Experience with Apache Spark or Databricks
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