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Open nowPosted today

Data Scientist

MyCareersFuture95,724 open roles

Pay
SGD 2,500 – SGD 4,000 a month
Where
North, Singapore
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Your applicationOpen nowData ScientistMyCareersFuture · North, Singapore

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

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  4. CV RocketApplied on MyCareersFuture's own form.

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The clock on this job

Early applications get read.

9.5% of postings close within 7 days. Measured by our own scanner across the market. MyCareersFuture postings stay open a median of 7 days.

Share of postings closed within
  1. 1.8%1 day
  2. 4.0%3 days
  3. 9.5%7 days
  4. 15.6%14 days
  5. 33.9%30 days
This job: posted today

MyCareersFuture median: 7 days open

The posting

Key Responsibilities:

  • Analyse large operational datasets to identify patterns, anomalies, outliers and risk indicators.
  • Develop approaches for anomaly detection, clustering, segmentation and risk scoring.
  • Build supervised machine-learning models where historical outcomes or labelled cases are available.
  • Perform feature engineering using structured and unstructured data.
  • Design evaluation approaches to assess model performance, including precision, recall, false positives and false negatives.
  • Work with domain experts to determine how analytical outputs should be incorporated into operational workflows.
  • Build and maintain data-processing and feature pipelines to support modelling at scale.
  • Develop production-ready model or scoring pipelines and integrate them with applications built by the delivery teams.
  • Monitor model performance, data quality and data drift after deployment.
  • Conduct exploratory analysis to identify new opportunities for workflow redesign and automation.
  • Support the use of LLMs and other AI techniques alongside traditional statistical and machine-learning approaches where appropriate.
  • Develop reusable analytical approaches and components that can be applied across multiple project engagements.

Requirements & Qualifications

  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related discipline.
  • 3–5 years of relevant experience in data science, machine learning, advanced analytics, or a similar role.
  • Experience working with large, messy operational or transactional datasets.
  • Experience in applied data science, including statistics, feature engineering, machine learning and model evaluation.
  • Experience with techniques such as anomaly detection, classification, clustering or risk modelling.
  • Experience building data pipelines and taking models beyond experimentation into production environments.

B. Technical & Professional Competencies

Essential (Must-Have)

  • Strong proficiency in Python and SQL.
  • Able to translate a business or operational problem into an analytical problem and determine the appropriate modelling approach.
  • Familiarity with software engineering practices including Git, automated testing and APIs.
  • Comfortable assessing model trade-offs and explaining them clearly to non-technical stakeholders.

Preferred (Advantageous)

  • Familiarity with containers, CI/CD or other DevOps / ModelOps practices would be advantageous.

C. Soft Skills & Communication Attributes

  • Able to work independently in an ambiguous, fast-moving environment and collaborate closely with engineers, product teams and domain experts.
  • Strong sense of ownership for turning analysis into something that is used in an operational workflow.
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