AvePoint - Data Scientist (EDB)

Singapore6mo ago

Requirements

• To perform this role, you must have/ be: • Minimum of Bachelor’s Degree in Computer Science, Computer Engineering, Machine Learning / Data Science / AI or related disciplines; • Able to understand and apply a range of AI/ML techniques for regression and classification • Familiar with popular python packages ( e.g. pandas, matplotlib, scikit-learn, XGBoost, NLTK, spaCy ) • Understanding of LLM concepts (e.g. context windows, embeddings, chunking, token management) and architectures (e.g. RAG) • Experience with context engineering techniques and prompt optimization strategies • Proficient in git, SQL • Proficient in Business Intelligence tools (e.g. Tableau, Qlik, MS PowerBI, Microstrategy) • Bonus skillsets which will allow you to excel in this role include: • Proficient in modern programming languages (e.g. typescript, C#) • Experience in cloud platform and services preferably in AWS • Experience in Docker/Kubernetes • Experience with web frameworks and full-stack development, including backend frameworks (e.g. FastAPI, Flask, Express.js) and RESTful API development, and frontend technologies (e.g. React, Vue.js, HTML/CSS, TypeScript) • Experience with LLM frameworks (e.g. LangChain, LlamaIndex, Hugging Face Transformers) • Knowledge of vector databases and embedding techniques (e.g. Pinecone, Chroma, FAISS) • Understanding of AI agent frameworks and multi-agent systems • Strong presentation skills and ability to explain technical concepts clearly to a non-technical audience • Proficient in statistical software tools (e.g. R, SAS) • Any personal data you share with us during the application process will be processed strictly in compliance with applicable data protection laws and our Privacy Notice.

Responsibilities

• Collaborating with business users to understand their key priorities and use cases; proposing and developing solutions using data science and/or Generative AI techniques to drive business value • Researching emerging AI/data science techniques and identifying relevant ones for EDB to explore and adopt (e.g. Agentic, LLM, Predictive, Fraud/Anomaly Detection, Text Analytics, Customer Segmentation) • Data wrangling & analysis - preprocessing, cleaning and feature engineering • Supporting the daily operations and maintenance of deployed data science models and products, including Assistants on PAIR / AIBots • Developing backend APIs and services to support AI model deployment and integration • Building frontend interfaces and user experiences for AI-powered applications • Documenting changes to existing products • Reviewing and implementing fixes for reported security vulnerabilities;