#EG Data Scientist (1 year contract)

NCS; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

NCS in Singapore seeks a Data Scientist to design, develop and deploy advanced analytics and ML solutions across industries. You will translate business challenges into production-ready data science work, collaborating with stakeholders and engineering teams to deliver impact.

You will apply statistics, NLP, optimisation, and simulation, building scalable models and dashboards. Expect mentorship, client advisory duties, and cross-functional collaboration in a fast-paced environment.

Qualifications

• Strong ability to communicate complex quantitative analysis in a concise, actionable manner.
• Experience with high-volume, high-dimensional structured and unstructured data.
• 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 visualization tools and libraries (Tableau, Qlik, Plotly, ggplot2, Shiny).
• Experience in model deployment and lifecycle management using Docker and Kubernetes.

Responsibilities

• 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 to deployment.
• Apply statistical analysis, machine learning, NLP, optimisation, and simulation techniques to solve problems.
• Perform statistically sound model validation and justify model performance.
• Build scalable ML models for production deployment and monitoring.
• Operationalise analytics workflows using Python/R and distributed processing frameworks like Spark.
• Deploy and manage models using containerisation with Docker and orchestration with Kubernetes.
• Leverage LLMs to build GenAI or Agentic AI solutions where appropriate.
• Design impactful dashboards and visualisations to communicate actionable insights.
• Present results to technical and non-technical audiences; act as adviser to clients.
• Collaborate with project managers and technical leads on analytics requirements.
• Contribute to data architecture and engineering decisions supporting analytics use cases.
• Participate in Agile or Waterfall projects and internal communities.
• Mentor and upskill junior data scientists and peers.

Skills

Communication

Data analysis

Feature engineering

Machine learning

Statistics

NLP

Optimization

Simulation

Python

R

Apache Spark

LLMs / GenAI

Data visualization

Docker

Kubernetes

Education

Master's degree in Mathematics/Statistics/Business Analytics

PhD preferred

Tools

Tableau

Qlik

Plotly

ggplot2

Shiny

Docker

Kubernetes

Apache Spark

Job 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.

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.

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.

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.

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 PhD) in Mathematics, Statistics, Business Analytics, or a related field.

Prior consulting experience in AI and data analytics domains.

Experience delivering advanced analytics solutions or conducting applied research.

Exposure to cloud and big data platforms (AWS, Azure, Hadoop, Spark, Cloudera).

Experience with DevOps practices in analytics delivery.

Background in application or software development.

Exposure to deep learning, reinforcement learning, or graph analytics.

Knowledge of database modelling and data warehousing concepts.

Additional Information

Why Join NCS

Lead high-impact Data & AI advisory programs for major enterprises and public sector clients.

Shape enterprise strategies and governance frameworks that drive real transformation.

Work with a talented, multidisciplinary team in a collaborative environment.

Competitive compensation and strong professional development support.

We are driven by our AEIOU beliefs - Adventure, Excellence, Integrity, Ownership, and Unity and we seek individuals who embody these values in both their professional and personal lives. We are committed to our Impact: Valuing our clients, Growing our people, and Creating our future.

Together, we make the extraordinary happen.

Learn more about us at ncs.co and visit our LinkedIn career site.