Search - Workchat - Senior Data Scientist

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. Elastic’s cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role 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 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. What You Will Be Doing 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. What You Will Bring 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/ ), 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. If this sounds interesting, we would love to hear from you Please include whatever info you believe is relevant: resume, GitHub profile, code samples, blog posts and writing samples, links to personal projects, etc. Compensation for this role is in the form of base salary. This role does not have a variable compensation component. The typical starting salary range for new hires in this role is listed below. These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the ranges may be modified in the future. An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs. Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program. Our total rewards package also includes a company-matched Registered Retirement Savings Plan (RRSP) with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being. The typical starting salary range for this role is: $128,300—$203,000 CAD Additional Information As a distributed company, diversity drives our identity. Elastic is an equal opportunity employer and is committed to creating an inclusive culture that celebrates different perspectives, experiences, and backgrounds. We welcome individuals with disabilities and strive to create an accessible and inclusive experience for all individuals. To request an accommodation during the application or the recruiting process, please email We will reply to your request within 24 business hours of submission. We are an equal opportunity/affirmative action employer committed to diversity, equity, and inclusion. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender identity or expression, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation. Please see here for our Privacy Statement. #J-18808-Ljbffr