Beta Labs was born out of The Lane Crawford Joyce Group, serving the most iconic clients in the retail industry specifically in fashion, beauty, and lifestyle businesses. We helped brands and retailers with presence in Southeast Asia and Greater China region with Analytics and AI / Machine Learning to achieve operational excellence and personalised customer experience, solving AI / Machine Learning problems on customer personalisation (e.g. Recommender) and optimisation (e.g. Supply Chain – Planning and Merchandising). We aim to develop new data products, which can be the best in Asia tackling retail vertical business problems.

The Lane Crawford Joyce Group is Asia’s pre-eminent luxury lifestyle Group, with more than 450 points of sale and 1.5 million active luxury customers across Greater China and online. Its companies are internationally recognised as benchmarks for retail innovation and creativity. Business Units: Lane Crawford, Joyce Fashion, Joyce Beauty, Pedder Group, ImagineX, Christian Louboutin, Alexander Wang, Sacai, Brooks Brothers, Canada Goose, Club Monaco, Aveda, Augustinus Bader, and more. The Group is affiliated with Wharf, Wheelock, and CitySuper, which are the leading retail conglomerate in Asia across malls, properties, supermarket, and hospitality, if not global.

You will be working with the best and like-minded data talent in town from McKinsey, Asia Miles, Deloitte Digital, Amazon, and with the modern big data infrastructure on Hadoop and Spark. Our research team has published more than 30 papers.

You should possess an entrepreneurial spirit and are passionate about Machine Learning Engineer / Software Engineer with a focus on the end user, we’d like to hear from you. You have to be comfortable dealing with ambiguity and working in a fast-paced environment.

Being the Machine Learning Engineer/ Software Engineer, the right candidate will

• Engineering machine learning models for maximum performance, accuracy, reliability, and scalability
• Deploy and integrate ML models in a web-based cloud solution
• Design, develop, and test decision optimisation machine learning models
• Give suggestions on ML strategy for the team and work closely with the data management and engineering team
• Track record of shipping data products: being able to write production level data science code while also conceptually understanding tradeoffs in production systems
• Understand and transform machine learning prototypes into scalable production-grade data products
• Design model training workflow and data pipeline, and work with data management and engineering team on implementation

YOU NEED TO BE ...

• 2+ years of hands-on experience in Python/C/C++ development and knowledge of distributed, scalable architectures
• You have hands-on experience implementing and maintaining large-scale, production ML systems in Python, Scala, or similar languages
• You might have experience in either recommender or knowledge systems
• Familiar with data structures and machine learning algorithms
• Strong modelling and inference skills
• MPhil / MSc / PhD in mathematics, computer science, engineering, operations research, physics, economics, etc.
• Hands-on experience with customer-centric and / or forecasting machine learning models
• Work experience in martech / retail / consumer business / supply chain is a plus
• Strong grasp of ML foundations (supervised learning, bias/variance trade-off) and strong interest in deep learning / reinforcement learning and experience with basic neural network architectures
• Proficient at one or more programming languages, e.g. Python, R, Java, C++, etc.
• Comfortable with SQL and ability to wrangle data from various sources
• While prior experience with big data technologies is not necessary (Hadoop, Hive, Spark), having a desire to learn such tools is something we look for
• You will design algorithm, train model and deploy to production. You will lead other data scientists to work with engineers and product managers to deliver end-to-end experience. You will collaborate across the company including research teams to adopt the latest technologies in AI and ML. You will come up with innovative solutions to address customer challenges.
• You will be part of the core team members that design, create and fine tune models. This work will include tasks such as proposing ML models to solve different scenarios, validating, choosing and fine tuning them.