Xephyr

Senior Data Scientist

Xephyr

full-time

Posted on:

Location Type: Hybrid

Location: Melbourne • Australia

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Job Level

Senior

Tech Stack

AzureCloudPythonSQL

About the role

  • Act as a trusted technical advisor to clients, including senior and C-suite stakeholders, across AI Readiness and delivery engagements.
  • Lead the delivery of AI Readiness Audits, helping clients assess their data, tooling, capability and governance posture.
  • Own end-to-end project and stakeholder management on engagements, including scoping, planning, timelines, risk and status reporting.
  • Own solution architecture for ML and Generative AI work, including model selection, tool choice and production readiness.
  • Design, build and deploy GenAI and ML solutions, including RAG, agentic systems, evaluation pipelines and guardrails alongside the engineering team.
  • Ensure solutions are production-ready with appropriate LLMOps and MLOps practices: monitoring, evaluation, cost and latency trade-offs.
  • Translate ambiguous client problems into scoped opportunities and contribute to estimates, proposals and statements of work.
  • Support the sales motion through discovery sessions, workshops and technical pitches.
  • Mentor mid and junior data scientists through code reviews, pairing, design reviews and knowledge sharing.
  • Feed insights, patterns and reusable components from client work back into Xephyr’s GenAI product roadmap.

Requirements

  • 5 to 10 years in data science, ML or applied AI, with a track record of shipping solutions into production.
  • Hands-on production GenAI experience: RAG, agents, tool use, evaluations and guardrails.
  • Fluent with the modern GenAI stack (e.g. LangGraph or equivalent, LlamaIndex, vector DBs such as pgvector/Pinecone/Weaviate, evals frameworks like Ragas, Braintrust or LangSmith).
  • Solid foundations in classical ML, statistics, experimental design and causal inference.
  • Strong Python and SQL; comfortable with Git, CI/CD, testing and at least one major cloud AI platform (Snowflake, Bedrock, Vertex, Azure AI Foundry or Databricks).
  • Working knowledge of modern data platforms, pipelines, warehousing, governance and quality.
  • Demonstrated success working directly with clients; consulting or professional services background is a strong plus.
  • Confident running engagements end-to-end, managing scope, timelines and stakeholder expectations.
  • Clear communicator who can translate complex concepts for both technical teams and senior business stakeholders.
  • Thrives in fast-moving environments with shifting priorities, evolving toolkits and volatile POCs.
  • Tertiary qualifications in computer science, engineering, mathematics, statistics, physics or a related quantitative discipline. Postgraduate study in ML, AI or data science is a plus but not required.
Benefits
  • Professional development opportunities
  • Flexible work arrangements
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
data sciencemachine learningapplied AIGenAIPythonSQLGitCI/CDstatisticsexperimental design
Soft Skills
stakeholder managementcommunicationmentoringproject managementconsultingproblem-solvingadaptabilityclient engagementteam collaborationleadership
Certifications
tertiary qualifications in computer scienceengineeringmathematicsstatisticsphysics