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Kuala Lumpur, Malaysia
Onsite
Grow your career with us
Here at Averis, our common purpose is to improve lives by developing resources sustainably. Our people are crucial in helping us to realise our vision to be one of the best Global Business Solution (GBS) organization to support our customers in creating value for the Community, Country, Climate, Customer and Company.
Responsibilities:
Responsibilities:
Senior Data Scientist 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
I) 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.
II) 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.
II) 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.
IV) 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.
V) 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
• 5+ 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:
o SQL and relational databases (e.g., PostgreSQL or similar)
o Python for data manipulation and analysis
o Dashboarding and data storytelling fundamentals (tool-agnostic)
• Practical experience delivering at least one of the following in a production or near-production setting:
o Retrieval-Augmented Generation (RAG) using a vector database
o LLM-based structured extraction into JSON / schemas
o LLM integration via APIs into an end-user workflow
• Strong communication and stakeholder management skills; able to deliver iteratively in time-boxed
environments.
When you send us your resume and personal details, it is deemed you have provided your consent for us to keep or store your information in our database. All the information you have provided is only used for the recruitment process. Averis will only collect, use, process or disclose personal information where and when allowed to under applicable laws.
Only shortlisted candidates will be contacted for an interview. We endeavour to respond to every applicant. However, if you receive no response from us within 60 days, please consider your application for this specific position unsuccessful. We may contact you in the future if there are opportunities that match your qualifications and experience. Thank you for considering a career with Averis.
