全职 Senior Data Scientist (Advanced Insights) 工作, 薪水, Averis WP Kuala Lumpur 公司招聘中 - Ricebowl

Position Summary

The Senior Data Scientist (Advanced Insights) is responsible for transforming operational data into actionable insights that improve business performance. The role owns end-to-end delivery: problem framing, dataset and metric design, dashboard development, and the implementation of GenAI-enabled solutions that sit on top of governed enterprise data. The successful candidate is delivery-oriented, collaborative, and capable of shipping reliable solutions that are adopted by business users.

Key Responsibilities

1. Business & Decision Analytics

   • Partner with stakeholders to identify high-impact opportunities where analytics and GenAI improve decision-making and process performance.

   • Translate business needs into analytical questions, KPI definitions, reporting requirements, and GenAI user stories.

   • Manage a portfolio of deliverables with clear success measures and measurable outcomes.

2. Analytics Engineering & Metric Governance

   • Extract, clean, transform, and integrate data from multiple systems to produce trusted analytics datasets.

   • Design and maintain analytics data models (e.g., star schema / subject-area models) to support reporting and retrieval.

   • Define auditable metric logic and ensure consistency, data quality, and traceability of key measures.

3. Dashboards, Reporting & Data Storytelling

   • Design and develop operational dashboards and reports that clearly communicate performance, trends, and exceptions.

   • Present insights in business language with clear implications and recommended actions.

   • Iterate with users to improve usability, clarity, and adoption.

4. GenAI Solutions (RAG, Chat, Structured Extraction)

   • Design and implement GenAI workflows including RAG pipelines (ingestion, chunking, embeddings, retrieval, prompting).

   • Build document Q&A and structured extraction solutions (documents → fields/JSON) with validation and post-processing.

   • Build lightweight API services (e.g., FastAPI/Flask) to enable integration with internal systems and workflows.

5. Mentoring & Standards

   • Mentor junior analysts / team members on problem framing, SQL, data modelling, dashboard best practices, and GenAI evaluation hygiene.

   • Define and promote templates and standards for KPI definitions, dashboards, documentation, and evaluation.

Required Qualifications

• 6–8+ years of experience in data analytics, BI, data science, data engineering, or adjacent roles with end-to-end delivery ownership.

• Strong quantitative reasoning and ability to translate ambiguous business problems into structured analyses and decisions.

• Demonstrated proficiency in:

  • SQL and relational databases (e.g., PostgreSQL or similar)

  • Python for data manipulation and analysis

  • Dashboarding and data storytelling fundamentals (tool-agnostic)

• Practical experience delivering at least one of the following in a production or near-production setting:

  • Retrieval-Augmented Generation (RAG) using a vector database

  • LLM-based structured extraction into JSON / schemas

  • LLM integration via APIs into an end-user workflow

• Strong communication and stakeholder management skills; able to deliver iteratively in time-boxed environments.