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Open nowPosted 15 days ago

Data Scientist (AI/ML) | Contract | Financial Services

MyCareersFuture94,028 open roles

Pay
SGD 9,000 – SGD 13,000 a month
Where
Central, Singapore
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Your applicationOpen nowData Scientist (AI/ML) | Contract | Financial ServicesMyCareersFuture · Central, Singapore

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7.7% of postings close within 7 days. Measured by our own scanner across the market.

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  4. 14.0%14 days
  5. 33.7%30 days
This job: posted 15 days ago

The posting

Overview

We are looking for a highly skilled AI/ML Specialist to design and deliver advanced, scalable AI solutions that solve real-world business challenges.

In this role, you will be part of a high-performing, cross-functional team, driving innovation across areas such as Generative AI, Natural Language Processing (NLP), personalization, and predictive analytics. You will play a key role in building end-to-end AI solutions—from problem definition and data modelling to deployment at scale—while contributing to the organization’s broader AI strategy.

Responsibilities

  • Design and develop scalable AI/ML solutions across domains such as Generative AI, NLP, recommendation systems, and time series forecasting
  • Build end-to-end machine learning pipelines, from data collection and feature engineering to model development, validation, and production deployment
  • Research and apply state-of-the-art AI techniques to enhance existing solutions and solve emerging business problems
  • Define and implement deployment strategies for production-grade AI systems on cloud platforms
  • Drive technical design and architecture discussions, ensuring scalability, reliability, and performance
  • Maintain high standards of code quality, testing, and CI/CD integration
  • Collaborate closely with product, engineering, and business teams to translate requirements into technical solutions
  • Mentor junior team members and contribute to knowledge sharing within the team

Requirements

  • Master’s or PhD in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field
  • Minimum 3 years of hands-on experience building and deploying AI/ML solutions at scale
  • Expertise in at least one or more areas: Generative AI, NLP, Deep Learning, Reinforcement Learning, Recommendation Systems, or Time Series Forecasting
  • Proficiency in programming language such as Python, Java, Scala, or Julia
  • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, XGBoost)
  • Experience with ML lifecycle tools and platforms, such as Airflow, Kubeflow, MLflow, or similar
  • Familiarity with containerization and orchestration tools (Docker, Kubernetes)
  • Knowledge of model serving, observability, and monitoring tools (e.g., Prometheus, Grafana, Elasticsearch)
  • Solid understanding of software engineering best practices, including CI/CD and version control
  • Experience working in Agile environments with cross-functional teams
  • Good analytical thinking, problem-solving skills, and ability to translate business needs into technical solutions
  • Excellent communication and stakeholder management skills

Nice-to-Have

  • Experience with cloud platforms such as AWS or GCP
  • Exposure to feature stores (e.g., Feast, Hopsworks) and model formats (e.g., ONNX, PMML)
  • Research background with publications or patents in AI/ML-related fields

Interested candidates may send in their resume and cover letter directly to [email protected] (R1434374), stating the position as the subject title in the email.

Jireli Gem Mejia Cabria | EA License No. 02C3423 | Personnel Registration No. R1434374

Please note that your response to this advertisement and communications with us pursuant to this advertisement will constitute informed consent to the collection, use and/or disclosure of personal data by ManpowerGroup Singapore for the purpose of carrying out its business, in compliance with the relevant provisions of the Personal Data Protection Act 2012. To learn more about ManpowerGroup's Global Privacy Policy, please visit https://www.manpower.com.sg/privacy-policy

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