Work cross-functionally with business owners/product managers/engineers, and designers throughout the whole process of the data science projects, todiscover marketing and growth problems, uncover insights, identify key levers and build practical solutions based on large-scale user and product data.
Drive innovation by proposing new experimentation methodologies as well as novel statistical solutions and working closely with product team to facilitate the marketing business decision process.
Build core machine learning models as well as end-to-end machine learning pipeline to understand, identify and predict users' shopping behaviours across their entire shopping journey in order to optimise customer acquisition, engagement, conversion, experience and brand loyalty.
Translate quantitative data into actionable recommendations and to translate business objectives into marketing goals and measurements.
Masters or PhD in Computer Science, Engineering, Mathematics, Statistics, Biostatistics or fields related to data mining preferred.
2+ years of industry experience in at least one programming language (e.g., Python, Golang, Scala) and Unix/Linux system and comfortable working with large datasets and conducting complex data analysis using SQL, Python or R.
Good knowledge in statistical methods, classical machine learning (classification, regression, clustering, etc), deep learning, reinforcement learning.
Experience in Tensorflow/Pytorch machine learning framework, distributed data processing framework (e.g., Hadoop, Spark) and conducting production environment A/B test.Experience of marketing domain knowledge and concepts:
marketing mix modelling, propensity modelling,customer lifecycle management, CRM, customer segmentation, membership management, cross-sell and up-sell preferred.
Good communication skills with demonstrated ability to deliver and explain technical content to stakeholders and teamwork mindset.
Ability to deliver on tight timelines and work closely with cross-functional teams.
Preference will be given to candidates with the following additional requirements as below
Ability to write production-level code in Python, Golang or Scala and practical development experience in deploying real-time model serving in production.
Practical development experience in NoSQL database like Cassandra, ScyllaDB, Redis.
- Work cross-functionally with business owners/product managers/engineers, and designers throughout the whole process of the data science projects, todiscover marketing and growth problems, uncover insights, identify key levers and