Senior Data Scientist, Elastic

Search, Workchat

$133.1-252.9k

Salary is dependent on location and is benchmarked on US rates and may vary in other locations; + Participate in Elastic's stock program

Python

Elasticsearch

Pandas

PyTorch

Senior level

London

Remote from Spain, UK, US

Software that searches and analyses data in real time

Open for applications

Software that searches and analyses data in real time

1001+ employees

B2BAnalyticsSaaS

Open for applications

$133.1-252.9k

Salary is dependent on location and is benchmarked on US rates and may vary in other locations; + Participate in Elastic's stock program

Python

Elasticsearch

Pandas

PyTorch

Senior level

London

Remote from Spain, UK, US

1001+ employees

B2BAnalyticsSaaS

Company mission

To build software to make data usable in real-time and at scale for search, logging, security, and analytics use cases.

Job

Company

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

Top investors

8% employee growth in 12 months

Glassdoor (3.8)

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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