Skip to sign up

Job matched to your search

#EG Data Scientist

NCS · Singapore

Singapore · On-siteFull-TimePosted Jun 17, 2026

Free · Join 5,000+ job seekers using Qarera

How well do you match this role?

Tap the skills you already have — then see your real match score, what’s missing, and your resume fixed for this job.

↑ tap the skills you have
Loading sign-in…
Free · no credit card · 30 seconds

Job description

Date: 2026-06-17

Location: Singapore, , Singapore

Company: NCS

Job Requisition ID: 172630

Company Description

NCS is a leading AI Tech Services company. With a 15,000-strong team across the Asia Pacific, NCS scales its platforms and capabilities to provide clients with greater agility and AI expertise across a range of Industries. Embracing a strong ecosystem of global partners, NCS transforms technology services delivery combining AI with digital resilience to drive real business impact. NCS is a subsidiary of the Singtel Group.

Job Description

As a Data Scientist, you will design, develop, and deploy advanced analytics and machine learning solutions that uncover hidden insights from large, complex datasets. You will work closely with business stakeholders, project managers, and engineering teams to translate real-world business challenges into production-ready data science solutions. This role combines hands-on analytics development, applied research, and client advisory responsibilities, supporting organisations on their data science and AI journey.

What will you do?

Applied Data Science & Advanced Analytics

  • Translate customer pain points into clear analytical problem statements and solution architectures.
  • Design, build, and iterate end-to-end data science workflows, from data ingestion and preprocessing to feature engineering, modelling, and deployment.
  • Apply statistical analysis, machine learning, NLP, optimisation, and simulation techniques to solve complex business problems.
  • Perform statistically sound model validation and clearly justify model selection and performance.

Model Engineering & Production Deployment

  • Build scalable, efficient machine learning models for deployment in production systems.
  • Operationalise analytics workflows using Python/R and distributed processing frameworks such as Apache Spark.
  • Deploy and manage models using containerisation and orchestration tools (e.g. Docker, Kubernetes).
  • Leverage LLMs to build GenAI or Agentic AI solutions where appropriate.

Insights Communication & Visualisation

  • Design and develop impactful dashboards and visualisations to communicate actionable insights.
  • Present results, learnings, and recommendations clearly to both technical and non-technical audiences.
  • Act as a trusted adviser to clients in conceptualising and evaluating advanced analytics solutions.

Collaboration & Delivery

  • Work closely with project managers and technical leads to provide regular status updates and refine analytics requirements.
  • Contribute to data architecture and engineering decisions that support analytics use cases.
  • Participate in interdisciplinary teams delivering projects using Agile or Waterfall methodologies.

Knowledge Sharing & Mentorship

  • Contribute to internal communities of practice and special interest groups.
  • Mentor and upskill junior data scientists and peers, depending on seniority.

Qualifications

The ideal candidate should possess:

Must-have

  • Strong ability to communicate complex quantitative analysis in a concise, actionable manner.
  • Proven experience working with high-volume, high-dimensional structured and unstructured data.
  • Strong expertise in feature selection and feature engineering across diverse data types.
  • Solid grounding in machine learning techniques (supervised and unsupervised).
  • Deep understanding of advanced analytics (statistics, NLP, optimisation, simulation).
  • Strong programming skills in Python and/or R; experience with Apache Spark or similar frameworks.
  • Experience using LLMs for GenAI or Agentic AI solution development.
  • Hands-on experience with data visualisation tools and libraries (e.g. Tableau, Qlik, Plotly, ggplot2, Shiny).
  • Experience in model deployment and lifecycle management using Docker and Kubernetes.

Nice to have

  • Postgraduate degree (Master’s or

Don’t just read the job — see if you’ll get it.

Get your match score, a resume tailored to this exact role, and jobs like it — free.

Check my fit for this job
Loading sign-in…
Apply →