Data Scientist with Software Engineering
Summary
Builds and integrates ML models for data generation and privacy, writes Python code, and collaborates with engineers to deploy models via REST APIs on cloud platforms.
Job Role : - Data Scientist with Software Engineering
Job Location:
- Singapore
Experience:
- 2-3 Years
Roles and Responsibilities: Design, develop, and experiment with machine learning models, particularly for data generation and privacy-focused applications. Conduct model evaluation, performance tuning, and troubleshooting for diverse data types and scenarios. Collaborate with software engineering teams to develop and integrate machine learning features into production-ready systems. Build and optimize data pipelines, preprocessing workflows, and privacy metrics. Diagnose and resolve issues related to model performance, integration, or user feedback. Document model designs, parameters, and evaluation methods in a clear and user-friendly manner. Participate in Agile development practices, including code reviews, sprint planning, and design discussions.
Skills and Requirements: Bachelors degree or higher in Computer Science, Data Science, or a related field. 23 years of professional experience in data science, applied machine learning, or related areas. Strong programming skills in
Python , with experience using ML frameworks such as
PyTorch ,
TensorFlow , or
scikit-learn . Understanding of
backend development
concepts (REST APIs, FastAPI, Flask, or similar). Familiarity with
cloud platforms
(e.g., AWS) and
version control systems
(Git). Strong analytical and problem-solving skills with the ability to design and evaluate experiments. Excellent communication skills to explain technical concepts to technical and non-technical audiences. Ability to work collaboratively in multidisciplinary and Agile environments.
Job Location:
- Singapore
Experience:
- 2-3 Years
Roles and Responsibilities: Design, develop, and experiment with machine learning models, particularly for data generation and privacy-focused applications. Conduct model evaluation, performance tuning, and troubleshooting for diverse data types and scenarios. Collaborate with software engineering teams to develop and integrate machine learning features into production-ready systems. Build and optimize data pipelines, preprocessing workflows, and privacy metrics. Diagnose and resolve issues related to model performance, integration, or user feedback. Document model designs, parameters, and evaluation methods in a clear and user-friendly manner. Participate in Agile development practices, including code reviews, sprint planning, and design discussions.
Skills and Requirements: Bachelors degree or higher in Computer Science, Data Science, or a related field. 23 years of professional experience in data science, applied machine learning, or related areas. Strong programming skills in
Python , with experience using ML frameworks such as
PyTorch ,
TensorFlow , or
scikit-learn . Understanding of
backend development
concepts (REST APIs, FastAPI, Flask, or similar). Familiarity with
cloud platforms
(e.g., AWS) and
version control systems
(Git). Strong analytical and problem-solving skills with the ability to design and evaluate experiments. Excellent communication skills to explain technical concepts to technical and non-technical audiences. Ability to work collaboratively in multidisciplinary and Agile environments.