Search - Agent Builder - Senior Data Scientist

PowerToFly; Remote; CAD 128,000 - 203,000; Full time

Job summary

A leading technology firm in Canada is seeking a Senior Data Scientist to enhance conversational search capabilities. The role involves designing evaluation pipelines and collaborating with cross-functional teams. The ideal candidate has 5-8 years of experience in data science, proficient in Python and machine learning frameworks, and must contribute to product decisions based on analytical results. This position offers competitive compensation and a flexible work environment.

Benefits

Competitive pay based on role

Health coverage for you and your family

Flexible locations and schedules

Generous number of vacation days

Parental leave of 16 weeks

401(k) / Retirement Plan

Qualifications

• 5–8 years in applied Data Science/Machine Learning with strong IR/NLP experience.
• Experience in designing evaluation pipelines for conversational search.
• Strong written communication and low-ego collaboration.

Responsibilities

• Design and maintain evaluation pipelines for conversational search.
• Build and compare retrieval & re-ranking baselines.
• Use results to drive product decisions with clear metrics.
• Instrument dashboards and telemetry for performance visibility.
• Collaborate closely with backend engineers and product teams.
• Share outcomes clearly and mentor peers in experiment design.

Skills

Applied Data Science/Machine Learning

Information Retrieval/Natural Language Processing

Proficiency in Python

Hands-on evaluation expertise

Practical Elasticsearch experience

Tools

PyTorch

Pandas

MLflow

Job description

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, 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—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 behaviours, 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 visualisations 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.

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.

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 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/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.

Additional Information – We Take Care of Our People:

As a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn’t matter if you’re just out of college or your children are; we need you for what you can do.

We strive to have parity of benefits across regions, and while regulations differ from place to place, we believe taking care of our people is the right thing to do.

• Competitive pay based on the work you do here and not your previous salary
• Health coverage for you and your family in many locations
• Ability to craft your calendar with flexible locations and schedules for many roles
• Generous number of vacation days each year
• Increase your impact – We match up to $2000 (or local currency equivalent) for financial donations and service
• Up to 40 hours each year to use toward volunteer projects you love
• Embracing parenthood with a minimum of 16 weeks of parental leave

Different people approach problems differently. We need that. Elastic is an equal opportunity employer and is committed to creating an inclusive culture that celebrates different perspectives, experiences, and backgrounds. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation.

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 [e-mail]. We will reply to your request within 24 business hours of submission.

Applicants have rights under Federal Employment Laws and can view the following posters linked below:

Family and Medical Leave Act (FMLA) Poster

Employee Polygraph Protection Act (EPPA) Poster

Elasticsearch develops and distributes technology and information that is subject to U.S. and other country export controls and licensing requirements for individuals who are located in or are nationals of the following sanctioned countries and regions: Belarus, Cuba, Iran, North Korea, Russia, Syria, the Crimea Region of Ukraine, the Donetsk People’s Republic (\"DNR\"), and the Luhansk People’s Republic (\"LNR\"). If you are located in or are a national of one of the listed countries or regions, an export license may be required as a condition of your employment in this role. Please note that national origin and/or nationality do not affect eligibility for employment with Elastic.

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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.

The typical starting salary range for this role is:

$128,300—$203,000 CAD

What Elastic Has to Offer

Elastic is the company behind the Elastic Stack - Elasticsearch, Kibana, Beats, and Logstash. From stock quotes to Twitter streams, Apache logs to WordPress blogs, Elastic helps people explore and analyze their data differently using the power of search. Thousands of organizations worldwide, including Cisco, eBay, Goldman Sachs, Microsoft, The Mayo Clinic, NASA, The New York Times, Wikipedia, and Verizon, use Elastic to power mission-critical systems. Elastic offers their employees benefits like:

• 401(k) / Retirement Plan
• Minimum 16 weeks of parental leave
• Health coverage & vision insurance
• Flexible locations & schedules
• Work from home policy
• Generous vacation time & paid holidays