Data Scientist

Description Data Scientist (ML / Software Engineering background)At Alphaeus Pte Ltd, we are seeking an exceptional Data Scientist with a background in Machine Learning and Software Engineering to join our dynamic team. As a full-time Data Scientist, you will play a crucial role in driving our data-driven initiatives and leveraging cutting-edge technologies to solve complex business challenges. This position is based in the Central Region and offers the opportunity to work on exciting projects that directly impact our company's growth and success. This role will be at the intersection of data science, applied machine learning, and software engineering. You will be involved in: 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. 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. Applied Research & Experimentation Familiarity with reading, synthesizing, and ability to translate emerging research into practical prototypes. 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. 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. #J-18808-Ljbffr Industry Other Category IT & Technology Sub Category Software Architecture & Engineering