Global Fashion Group ("GFG") is the #1 online fashion platform for emerging markets. It operates across four continents and 25 countries and employs over 9,000 people via its five brands / ventures: ZALORA in Southeast Asia, THE ICONIC in Australia and New Zealand, DAFITI in Brazil/Latam and LAMODA in Russia/Ukraine/Kazakhstan/Belarus.
At GFG, technology is core to long-term success and is a crucial enabler of a great Customer Experience. We're a mix of experts in fashion, logistics, data analytics, marketing, and design, guided by business consultants and tech geniuses – everyone contributes to the success of GFG and the ventures.
- "We Dream Big" – You will challenge the status quo, bringing passion, innovation and creativity to the wider GFG team.
- "We Are True to our Customers" – You will be inherently passionate about customer impact, both external and internal customers, and will constantly challenge yourself and the team to deliver more customer value
- "We Get Things Done" – You do not want to work in a cumbersome organisation, you want to work in an agile high-growth company. You lead with the right balance of planning and pragmatism.
- "We are Stronger Together" - You will be part of an experienced team working collaboratively to inspire the broader organisation towards a united vision.
About the Role The Data Team is an integral part of GFG team and is essential to enable a data-driven decision making culture. The Data team sits at the cross-roads of various departments ranging from Category Management (Buying & Planning), Finance, Customer Service, Marketing & Fulfilment Centre. It is an exciting place to be and allows us to provide unique insights about the business, its environment and the marketplace. As a predictor and forecaster of the future, it also is undoubtedly a valued and significant role.
We are looking for an experienced Data leader to lead one of the three data areas in the business - the Internal Products Data function which encompasses all tech products and services built for our internal customers - our employees. You will be part of the largest data area and a highly innovative team working on interesting and difficult problems, leveraging cutting edge technology to build solutions and employee facing data products.
Your work will have a direct impact on shaping the future of how all the operations and decisions are enabled across 14 countries around the world, and will help run the group more efficiently and be on the leading edge of offering a seamless customer experience. The ideal candidate will have a strong quantitative or technical background with experience working with large datasets and solving tough problems. You will be a highly intelligent self-starter, with a bias towards action and attention to detail, reporting to the Director of Data Science.
Who are we looking for? A senior and well experienced Data Science practitioner with considerable years of experience - who has done their time in the dark deep mines of data, built live production-ready algorithms at scale, hired, grown and maintained data science teams and most importantly has a passion for enabling data driven decision making for the wider business through the art of data empathy. This role will lead a large team of data scientists and also requires hands-on work to get stuff done.
What will you be doing? At GFG, we'd like to think of our Data leader as a builder-at-heart doing all of the three functions described below. Each aspect broadly covers your day to day work, as well as how it serves the company needs. These three pillars serve to act as the cornerstones of this senior role.
This is quite a unique role and one that opens up opportunities to work across the cross section of the business as the key stakeholder of data driven decision making in these areas.
You'll be the key owner of diverse areas using data ranging from Category Management team buying and planning merchandising, to the Fulfilment Center optimising every single inch of warehouse usage, to the Finance team finding the smartest way to forecast demand and supply, to the Customer Support team enabling our agents to deliver amazing customer service, and a few more that directly enable our employees to make smarter, faster and better decisions - which in turn leads us to be an amazing customer-focussed company.
BUILD
Experience with solving the following problems and building scalable solutions for a large company before on Supply Chain Analytics, Warehouse Optimisation, Financial Reconciliation and Customer Service Optimisation
Ability to build from ground-up and/or redesign existing demand forecasting and predictive techniques to be able to get a closer-to-reality version of the future - e.g. Demand Forecasting, Returns Prediction and Inventory Planning and Replenishment
Inculcate a Developer mindset to the application of data science in everyday business by practicing and preaching a reproducible, defensible and accuracy-driven approach
GUIDE
Lead a diverse team of 5-7 data scientists to deliver better value for the business by educating, enabling and emphasising the importance of empathising with business needs and delivering data products that create an impact
Create and foster a career guidance and development plan for the team by enabling them to see into the future both for themselves and for the larger company
Actively participate and contribute to hiring of new talent, recognising new opportunities for existing people to grow into and contribute to the evangelisation of data within the marketing areas of the business
STRATEGISE
Be an effective translator of math to english to deal with executive business stakeholders enabling them to make quicker and accurate decisions without being bogged down by numbers, graphs and minutiae - i.e get stuff done!
Take part in strategy sessions for half yearly and annual planning exercises and provide key inputs into how the strategy of the internal products area can be formulated using data as a lynchpin and actively look for new opportunities to use data better
Act as an always-on sounding board and source of knowledge for the key stakeholders in the wider business and senior leadership to brainstorm new ideas on the back of data and bring in knowledge from prior experience solving similar problems at scale
How will you be doing it?
With a confidence interval of 90%, if you can 'strictly' prove your skills in at least 4 of the 5, then you can easily be able to do most of what is stated above.
- Language - Proficient and well-defined knowledge of at least 1 statistical programming language - R or Python AND the one main data language - SQL
- Data - Ability to work with datasets of all shapes, sizes and textures - from 20 KB-200 PB
- Open Source - Experience with open source application usage for data processing and reporting purposes e.g. Apache Airflow, Apache Superset
- Presentation - Ability to produce spot-on business-ready output with key action items
- Maths - Proficient knowledge of statistics with a well displayed ability to build predictive models, forecasting approaches, simulation and personalisation algorithms
The zeroth skill that is expected as a default is an ability to program/code, along with the must-have skills of maintaining code quality and following standard software development life cycle of build -> test -> deploy using Git and a CI pipeline.
Extra points for the following great-to-haves:
- Experience with the online retail industry or any major e-commerce player
- Working knowledge of parallelisation processes and deep learning approaches
- Certification/knowledge of AWS and GCP solutions and prior experience with docker and container based deployments
- Contribution to the open source community and an advocate of using open source technologies to solve business problems
- Having built scalable data products for a business end user using the Agile methodology
Please respond back with two things - Simple yes/no for the 5 fundamental asks AND your updated resume that reflects these asks. Remember you just need to satisfy 4 of the 5 main asks. There is also a statistical solecism in the description above, can you find it?