Data Scientist

ENCORA TECHNOLOGIES PTE. LTD.; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

A leading technology firm in Singapore is seeking a Data Scientist to drive model development and product features while collaborating closely with software engineering teams. The successful candidate will have a Bachelor's degree and at least 2-3 years of experience in machine learning, programming in Python, and a solid understanding of data analytics frameworks. This role emphasizes both technical proficiency and communication skills, enabling effective knowledge sharing across teams.

Qualifications

• At least 2-3 years of relevant professional experience.
• Ability to analyze model behavior and diagnose training issues.
• Familiarity with collaborative coding practices.

Responsibilities

• Design and conduct experiments to evaluate emerging models.
• Collaborate with software engineers to build product features.
• Diagnose user issues and provide actionable fixes.
• Write user-facing documentation and translate complex concepts.

Skills

Machine learning proficiency

Python programming

Model development

Collaboration

Experimentation and diagnostics

Education

Bachelor's degree in Computer Science or related field

Tools

PyTorch

TensorFlow

scikit-learn

AWS

FastAPI

Job description

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 eva uate emerging SDG modes (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 MUDS 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. This could include 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 ability to translate emerging research into practical prototypes.

4. Software Engineering

• Working knowledge of backend development (REST APls, 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, Cl/CD, and collaborative coding best practices.

5. Nice-to-Haves

• Experience with privacy-enhancing techno ogies, anonymisa on, synthe c 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