Senior Data Scientist, Elastic
Search, Workchat
CA$128.3-203k
This role is currently eligible to participate in Elastic's stock program
Software that searches and analyses data in real time
Open for applications
Software that searches and analyses data in real time
1001+ employees
Open for applications
CA$128.3-203k
This role is currently eligible to participate in Elastic's stock program
1001+ employees
Company mission
To build software to make data usable in real-time and at scale for search, logging, security, and analytics use cases.
Role
Who you are
- 5–8 years in applied DS/ML with strong IR/NLP experience (RAG, dense/sparse retrieval, re-ranking, vector search)
- Proficiency in Python, PyTorch/Transformers, Pandas; reproducible experiments (e.g., MLflow), versioned datasets, and clean, reviewable code
- Hands-on evaluation expertise: offline metrics (nDCG/MRR/Recall@k), LLM-as-judge calibration, groundedness/citation scoring, and online A/B testing
- Experience turning experimental results into clear product calls (models, routing, tools) and communicating them crisply to cross-functional partners
- Practical Elasticsearch experience (or similar); ES|QL familiarity is a plus
- Comfort working in a distributed, async-first environment; strong written communication; low-ego collaboration
What the job involves
- The Search Conversational Experiences team builds Elastic’s new conversational (agentic) platform that lets customers chat with their own data in Elasticsearch
- We own the quality layer for RAG, agents and tools, retrieval/citations, streaming, memory, and—crucially—the evaluation signals that turn open-ended questions into grounded, reliable answers
- As a Senior Data Scientist, you’ll be part of a cross-functional team (backend, DS, PM, UX) driving chat quality end-to-end: designing and running evaluation pipelines, improving prompts and tool behaviors, and turning measurements into product decisions that customers can feel
- You’ll help tackle frontier problems—folding RAG and vector search into an agent’s knowledge base, dynamically enriching model context to boost groundedness, shaping agent routing and tool selection policies, lighting up agent-driven visualizations on top of Elasticsearch data, and exploring multimodality and reasoning strategies where they truly move the needle
- This is an applied role: you will prototype, evaluate, and partner with engineers to ship
- Design and maintain offline/online evaluation pipelines for conversational search: golden sets, rubric/LLM-as-judge calibration, groundedness/citation checks, and A/B tests
- Build and compare retrieval & re-ranking baselines (sparse + dense), query understanding, and semantic rewrites; land improvements with clear metrics
- Use results to drive product decisions: model selection, efficient agent routing, tool gating, and agent customization for Elastic use cases in search and beyond
- Instrument dashboards and telemetry so helpfulness, faithfulness, latency, and cost trade-offs are visible and trustworthy; guard against regressions in CI
- Collaborate tightly with backend engineers on contracts (ES|QL, citations, telemetry), and with PM/UX to translate findings into shipped features
- Share outcomes clearly (docs, notebooks, PRs) and mentor peers in experiment design and evaluation craft
Salary benchmarks
Our take
Elastic develops the Elastic Stack, an open-source set of tools that includes Elasticsearch, Kibana, Beats, and Logstash, designed for data search and analysis. It also offers X-Pack, which adds commercial features to the Elastic Stack, and Elastic Cloud, a suite of SaaS (Software-as-a-Service) products.
This technology is widely used by major companies like eBay, Wikipedia, Yelp, Uber, Lyft, Tinder, and Netflix, along with over 17,000 other organizations. It is applied in various use cases, including application and website search, enterprise search, logging, infrastructure monitoring, application performance management (APM), security analytics (enhancing SIEM applications), and business analytics.
Freddie
Company Specialist at Welcome to the Jungle
Insights
8% employee growth in 12 months
Company
Funding (last 2 of 4 rounds)
Jul 2016
$58m
SERIES D
Jun 2014
$70m
SERIES C
Total funding: $162m
Company benefits
- Toast to your health: Fully paid health coverage for you and your family, in many locations
- Craft your calendar: Flexible location and schedule for most roles
- Create space for you: Distributed by design workforce, plus generous number of vacation days each year
- Embrace parenthood: Minimum of 16 weeks of parental leave, plus generous family formation benefits
- Give back your time: 40 hours each year to use toward volunteering with organizations and causes you’re passionate about
- Amplify your impact: Double your charitable giving — we match donations up to $1500 USD (or local currency equivalent)
Company HQ
Union Square, San Francisco, CA
Leadership
Shay Banon
(Co-Founder & CTO)Previously held the position of Technology Director at GigaSpaces Technologies.
Simon Willnauer
(Co-Founder)Previously spent 13 years at The Apache Software Foundation, holding various positions such as VP Apache Lucene and Lucene Core Commiter and PMC Member.
Uri Boness
(Co-Founder)Previously worked as a Software Architect and Head of Search at Orange11 for 7 years.
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