Build statistical and machine learning models to analyse large (PB-scale) volume of customer data, uncovering valuable insights and patterns.
Design A/B tests and causal inference to measure the impact of different strategies on user behaviour and business outcomes.
Implement robust MLOps pipelines to automate the deployment, monitoring, and maintenance of models in production environments.
Collaborate with data team to scale infrastructure for future initiatives.
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.
Requirements
Bachelor's degree or higher in the quantitative field or equivalent (Statistics, Applied Mathematics, Computer Science etc).
3 - 5+ years of working experience in Data Science, machine learning and deep learning.
Proficient in processing large-scale datasets using Big Data technologies like Hadoop, Spark and Hive.
Proven track record of deploying Machine Learning and deep learning models (TensorFlow / PyTorch) into production environment.
Proven ability to execute A/B testing strategies and identifying best practices, with a commitment to mentoring others and adopting emerging technologies.
Preferred:
Prior experience developing recommendation systems in ecommerce, Web3 or similar high growth environment is highly valued.
Knowledge and affinity of GenAI libraries and toolsets such as HuggingFace, LangChain, RAGAS, etc is a plus.
