Senior Data Scientist

Fuku; Kuala Lumpur; On-site; MYR 180,000 - 300,000; Full time

Job summary

Fuku in Kuala Lumpur is seeking a Senior Data Scientist (Advanced Insights) to transform operational data into actionable insights. You will own end-to-end delivery from framing to dashboarding and GenAI-enabled solutions, built on governed enterprise data.

You will partner with stakeholders, design data models and metrics, and mentor analysts while ensuring reliable, adoptable results across the business. This role is based in Kuala Lumpur and offers impactful analytics leadership.

Qualifications

• 6–8+ years of experience in data analytics, BI, data science, data engineering, or related roles with end-to-end delivery ownership.
• Strong quantitative reasoning and ability to translate ambiguous business problems into structured analyses and decisions.
• SQL and relational databases (e.g., PostgreSQL or similar).
• Python for data manipulation and analysis.
• Dashboarding and data storytelling fundamentals (tool-agnostic).
• Production-ready experience with RAG using a vector database, LLM-based structured extraction into JSON/schemas, or API-driven integration.
• Strong communication and stakeholder management; able to deliver iteratively in time-boxed environments.

Responsibilities

• Partner with stakeholders to identify high-impact opportunities where analytics and GenAI can 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.
• Extract, clean, transform, and integrate data from multiple systems to produce trusted analytics datasets.
• Design and maintain analytics data models (e.g., star schema) to support reporting and data retrieval.
• Define auditable metric logic and ensure data quality and traceability of key measures.
• Design and develop operational dashboards and reports that clearly communicate performance, trends, and exceptions.
• Present insights in business language with clear implications and actions.
• Iterate with users to improve usability and adoption of dashboards and reports.
• Design and implement GenAI workflows, including RAG pipelines and document extraction; build lightweight API services for integration.
• Mentor junior analysts on problem framing, SQL, data modeling, and dashboard best practices; promote KPI templates and standards.

Skills

SQL

Relational databases

Python

Dashboarding & storytelling

RAG

LLM structured extraction

LLM API integration

Communication & stakeholder mgmt

Problem framing & analytics

Education

Degree in Computer Science / Math / Statistics / Engineering

Tools

Docker

CI/CD

FastAPI

Flask

AWS Bedrock

Vector stores (FAISS/Qdrant/Milvus/Pinecone)

PDF/XML/HTML parsing

Job description

About the role

We are seeking a Senior Data Scientist (Advanced Insights) to join our Kuala Lumpur office. This role is responsible for transforming operational data into actionable insights to enhance business performance. The successful candidate will manage end-to-end delivery, including problem framing, dataset and metric design, dashboard development, and the implementation of GenAI-enabled solutions built on governed enterprise data. The ideal candidate is delivery-oriented, collaborative, and skilled at delivering reliable solutions that are adopted by business users.

Key Responsibilities

Business & Decision Analytics

• Partner with stakeholders to identify high-impact opportunities where analytics and GenAI can 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.

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 data 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, highlighting clear implications and recommended actions.
• Iterate with users to improve usability, clarity, and adoption of dashboards and reports.

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 (converting documents to fields/JSON) with validation and post-processing.
• Develop lightweight API services (e.g., FastAPI, Flask) to enable integration with internal systems and workflows.

Mentoring & Standards

• Mentor junior analysts and 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 related 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.

Advantages / Preferred Qualifications

Education: Degree in Computer Science, Mathematics, Statistics, Engineering, or other STEM disciplines is an advantage.

Cloud: Experience with AWS services (including data/analytics services and/or AWS Bedrock) is an advantage.

Qualifications: Relevant AWS certifications (e.g., cloud practitioner, associate, professional, specialty) are an advantage.

Experience with vector stores (FAISS, Qdrant, Milvus, Pinecone) and retrieval tuning.

Experience with document formats and parsing (PDF, XML, HTML) and robust post-processing/validation approaches.

Familiarity with Docker, CI/CD, and basic observability/monitoring practices.

Exposure to security/privacy practices (PII handling, access controls).

Domain exposure in operations contexts (maintenance, supply chain, manufacturing, plantation/process industries).