Data Scientist / Machine Learning Engineer - Permanent Role

TALENTSIS PTE. LTD.; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

TALENTSIS PTE. LTD. in Singapore is seeking an experienced Machine Learning Engineer to translate business problems into analytical and ML solutions and to design, train, and optimise models in production.

You will collaborate with software engineering and DevOps teams, deploy APIs, monitor models, and continuously improve accuracy while staying current with AI advancements.

Qualifications

• 3+ years hands-on ML deployment & statistical analysis on large data sets.
• Experience translating business requirements into analytical ML solutions.
• Proficient in Python, SQL, data wrangling, data visualization, and DBMS.

Responsibilities

• Perform exploratory data analysis (EDA) to uncover trends and actionable insights from large datasets.
• Translate business problems into analytical and machine learning solutions.
• Design, develop, train, and optimise machine learning models and algorithms.
• Evaluate model performance using validation techniques, hyperparameter tuning, and optimisation methods.
• Deploy ML models into production environments and expose via APIs.
• Collaborate with software engineering and DevOps teams to build scalable, production-ready AI solutions.
• Monitor deployed models, troubleshoot issues, and improve model accuracy and efficiency.
• Present findings and recommendations clearly to technical and non-technical stakeholders.
• Stay current with AI/ML advancements and suggest new tools and best practices.

Skills

Python

SQL

Data Wrangling

Data Visualisation

Machine Learning

Model Deployment

Agile/Scrum

Tools

TensorFlow

PyTorch

SAS

Qlik Sense

Docker

Kubernetes

Job description

Key Responsibilities

• Perform exploratory data analysis (EDA) to uncover trends, patterns, and actionable insights from large datasets.
• Translate business problems into analytical and machine learning solutions.
• Design, develop, train, and optimise machine learning models and algorithms.
• Evaluate model performance using appropriate validation techniques, hyperparameter tuning, and model optimisation methods.
• Deploy machine learning models into production environments and integrate them with existing applications through APIs.
• Collaborate with software engineering and DevOps teams to build scalable, production-ready AI solutions.
• Monitor deployed models, troubleshoot issues, and continuously improve model accuracy and efficiency.
• Present analytical findings and recommendations clearly to both technical and non-technical stakeholders.
• Stay current with advancements in AI, machine learning, and data science, recommending new tools and best practices where applicable.

Requirements

• Minimum 3 years of hands-on experience in machine learning implementation, deployment, and statistical data analysis involving large datasets.
• Strong experience translating business requirements into analytical solutions using statistical and machine learning techniques.
• Proficient in:PythonSQLData WranglingData VisualisationDatabase Management Systems (DBMS)
• Experience with one or more of the following:TensorFlowPyTorchRSASQlik Sense
• Experience deploying machine learning models into production environments.
• Familiarity with Agile development methodologies such as Scrum is preferred.

Nice to Have

• Experience with any of the following technologies would be advantageous:
• Power BI
• Microsoft Access
• SharePoint
• Kubernetes
• Docker or Podman
• Microservices Architecture
• DevSecOps practices

Work Location: East / West

(EA Reg No: 20C0312)