About the Company
Strong work-life balance
Stable and low-turnover team
Positive team culture
Responsibilities
- Build statistical and machine learning models to analyse large (PB-scale) volume of customer data, uncovering valuable insights and patterns
- Design and implement experiments, including A/B tests and causal inference to measure the impact of different strategies, initiatives, and product changes on user behaviour and business outcomes
- Implement robust MLOps pipelines to automate the deployment, monitoring, and maintenance of models in production environments
- Effectively communicate complex findings and insights to both technical and non-technical stakeholders
- Stay updated with the latest advancements in AI and Generative AI technologies
- Build Big Data pipelines to support data science-related projects
Requirements
- Bachelor's degree or above in Statistics, Applied Mathematics, Computer Science or a related field
- 3-5+ years of working experience in Data Science, machine learning and deep learning
- In-depth understanding of machine learning and deep learning algorithms
- Hands-on experience in developing and deploying machine learning/deep learning models in production
- Experience with common analysis tools(SQL/ Python)
- Familiar and comfortable with large volumes of data and big data technology (Hadoop/Spark/Hive)
- Experience in using deep learning frameworks(Tensorflow/PyTorch)
- Solid technical & knowledge of A/B testing methodologies, can consistently explore and find the best practice
- Self-direction and willingness to both teach others and learn new techniques
- Knowledge and affinity of GenAI libraries and toolsets including HuggingFace, LangChain, RAGAS, and more is a plus
- Hands-on experience in RAG and fine-tune LLMs is a plus
- Have a strong ability to work under pressure, have the courage to overcome difficulties, and accept challenges
[Regrettably, only shortlisted candidates will be notified.]
Please note that data provided is for recruitment purposes only.
Business Registration No.: 202004228R | License. No. - 20S0118 | EA Registration No. -R 22106744
