Data Scientist (Software Engineering)

SAVANT INFOTECH SOLUTIONS PTE. LTD.; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

A technology solutions company in Singapore is looking for a Data Scientist to work at the intersection of data science and software engineering. The successful candidate will engage in model development, product feature collaboration, and documentation. Ideal applicants should have a Bachelor's degree, 2-3 years of experience, proficiency in Python, and machine learning expertise. Join an agile team aiming to integrate cutting-edge solutions to enhance products, ensuring a collaborative and innovative working environment.

Qualifications

• 2-3 years of relevant professional experience in data science or machine learning.
• Strong programming proficiency in Python.
• Hands-on experience in model development and experimentation.

Responsibilities

• Design and conduct experiments to evaluate emerging SDG models.
• Collaborate with software engineers to build product features that require ML/DS input.
• Work directly with users to diagnose issues with model training failures and outputs.

Skills

Machine learning foundation

Python programming

Model behavior analysis

Curiosity and willingness to learn

Strong communication skills

Education

Bachelor’s degree or higher in Computer Science, Data Science, Business Analytics or a related field

Tools

PyTorch

TensorFlow

scikit-learn

FastAPI

AWS

Job description

We are seeking a Data Scientist for Mirage, a web interface with API integration on the roadmap.

Job Scope

This role will be at the intersection of data science, applied machine learning, and software engineering.

You will be involved in:

1. Model Development
   • Design and conduct experiments to evaluate emerging SDG models (e.g., DDPM, ARF, Gaussian Copula).
   • Investigate failure cases (e.g., when models fail with certain data types, size, or cardinality).
   • Tune hyperparameters, refine architectures, and propose new modeling strategies.
2. Feature & Product Development
   • Collaborate with software engineers to build product features that require ML/DS input (e.g., imputation methods, handling of constraints, preprocessing pipelines).
   • Recommend and develop suitable approaches for features like single-/multi-column constraints, imputation strategies, and privacy metrics.
3. Diagnostics & Debugging
   • Work directly with users and the engineering team to diagnose user issues with training failures, poor outputs, or integration challenges.
   • Provide actionable fixes and communicate technical insights in a user-friendly way.
4. Documentation & Knowledge Sharing
   • Write user-facing documentation pages explaining model choice, hyperparameters, and utility/privacy metrics in a user-friendly manner.
   • Translate complex technical Data Science concepts into clear, approachable explanations.
5. Collaboration
   • Work closely with the SWE team (Next.js, FastAPI, AWS) to integrate the generation engine into production-ready systems.
   • Participate in Agile rituals, code reviews, and design discussions.

Requirements

1. Bachelor’s degree or higher in Computer Science, Data Science, Business Analytics or a related field, with at least 2-3 years of relevant professional experience.
2. Core Data Science & ML skillset
   • Strong foundation in machine learning with hands-on experience in model development and experimentation.
   • Strong programming proficiency in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
   • Ability to analyze model behavior, diagnose training issues, and design experiments to improve performance.
3. Applied Research & Experimentation
   • Familiarity with reading, synthesizing, and translating emerging research into practical prototypes.
4. Software Engineering
   • Working knowledge of backend development (REST APIs, FastAPI, Flask, or similar).
   • Comfortable working with cloud environments (AWS preferred).
   • Ability to debug and fix software-level issues when they affect ML workflows.
   • Familiarity with Git, CI/CD, and collaborative coding best practices.
5. Nice-to-Haves
   • Experience with privacy-enhancing technologies, anonymisation, synthetic data generation or differential privacy.
   • Familiarity with frontend integration workflows (Next.js/React).
   • Prior experience working in multi-disciplinary product teams.
6. Mindset & Collaboration
   • Curiosity and willingness to learn new domains (esp. data privacy).
   • Strong communication skills to explain technical concepts to both engineers and non-technical stakeholders.
   • Inclination to work in a collaborative, fast-moving Agile environment.