Global Fashion Group Global Fashion Group is the leading fashion and lifestyle destination in growth markets across LATAM, SEA and ANZ. From our people to our customers and partners, we exist to empower everyone to express their true selves through fashion. Our three e-commerce platforms – Dafiti, ZALORA and THE ICONIC – connect an assortment of international, local and own brands to over 800 million consumers from diverse cultures and lifestyles. GFG’s platforms provide seamless and inspiring customer experiences from discovery to delivery, powered by art & science that is infused with unparalleled local knowledge. As part of the Group’s vision we are committed to doing this responsibly by being people and planet positive across everything we do. Since launching in 2011, THE ICONIC has redefined the future of retail in Australia and New Zealand. As the leading fashion, sports and lifestyle e‑commerce destination in the region, our e‑commerce platforms (Retail, Marketplace and Services) provide a seamless and inspiring end‑to‑end customer experience through our own technology innovations. We stand for benchmark‑setting customer service, delivery options, returns policies, and curation of brands. We are a diverse and dynamic community of over 1,000 people working toward our purpose "To bring the future of shopping". THE ICONIC is people and planet positive, and we strive to create a positive impact in the world by driving genuine and meaningful change for the better of all communities involved. THE TEAM We are a small Data Science team at THE ICONIC – the largest online fashion retailer in AU/NZ. We build and ship real products end‑to‑end: LLM‑based agents, multi‑modal search, custom deep learning models at scale, and AI embedded directly into business workflows. Why join us? Deployed large‑scale LLMs into production, leveraging models like Google’s Gemini family Pioneered AI agents embedded directly into critical business workflows Launched multi‑modal search capabilities serving millions of customers Designed, trained, and deployed custom deep learning models on massive datasets, alongside advanced Markov models and hierarchical Bayesian systems Implemented generative AI for personalised recommendations, reshaping the customer experience Built robust infrastructure on Google Cloud, managing terabytes of carefully catalogued data Earned industry recognition, including the Retailer Awards CX Innovator Finalist and acknowledgements in the AFR All employees have access to our internal ChatGPT‑like platform with the industry's best conversational AI models If this sounds like a good fit, we would love to hear from you. Please include any GitHub repos or code samples in your resume. SCOPE OF ROLE Hands‑on data scientist who designs novel deep‑learning architectures when needed, ships pragmatic solutions otherwise, and owns end‑to‑end work Works autonomously on real problems with real users, making trade‑off decisions and shipping to production GitHub or Code Samples: candidates must provide links to production‑quality work; lack of evidence of strong coding proficiency may result in being not considered Who this role isn’t for? Those primarily interested in academic research or theoretical modelling without building real‑world software Those uncomfortable writing production‑quality code beyond notebooks Those not comfortable communicating fluently in English in a fast‑paced, global environment WHAT IT TAKES Strong English Communication Written and verbal fluency is essential. Participate in technical and product discussions, present solutions, and collaborate with the Australia‑based team and international stakeholders. ML Depth & Deep Learning Strong grasp of foundational ML concepts (classification/regression, feature engineering, evaluation metrics, training vs. inference, overfitting, etc.) Ability to design and train custom deep‑learning models, including comfort with novel or non‑standard architectures; judge when a custom approach is warranted Practical experience with deep‑learning frameworks (PyTorch, TensorFlow, or similar) and classical ML libraries (scikit‑learn, etc.) LLM & AI Agent Awareness Practical experience or informed perspective on building with LLMs – RAG pipelines, prompt engineering, agent architectures, evaluation of generative outputs Understanding of when LLMs are the right tool and when they aren’t Familiarity with failure modes: hallucination, grounding, cost/quality trade‑offs Python & Software Engineering Proficiency in Python with solid OOP fundamentals (classes, methods, inheritance) Good coding practices: exception handling, logging, clean structure Familiarity with functional programming concepts (basic understanding sufficient) Strong working knowledge of Git – branching, merging, pull requests, and conflict resolution Production Orientation Demonstrated ability to develop, debug, and ship code to live production environments Solid experience with Docker containers (building, running, debugging common pitfalls) Awareness of monitoring, latency, and failure modes beyond model accuracy Ways to stand out from the crowd Cloud Deployment: Experience deploying ML services on Google Cloud (Cloud Run, Vertex AI, or Kubernetes) CI/CD: Practical experience with GitHub Actions, Cloud Build, or similar Infrastructure as Code: Familiarity with Terraform or similar IaC tools A/B Testing: Experience designing experiments, interpreting results, and connecting them to product decisions Beyond the checklist The requirements above get you in the door. We also care about how you approach problems you haven’t seen before, whether your curiosity has taken you into unfamiliar territory, and how you handle the practical reality of building things for real users. WHAT WE OFFER YOU The ability to cross‑train into DevOps/Platforms or Data Engineering The unique opportunity to have a serious impact on a growing organisation A dynamic working environment shaping the face of fashion e‑commerce in growth markets Work closely with a global talent pool with an international mindset Best practice scaled agile engineering Amazing office and great culture: Massage chairs, table tennis, video game room, quarterly team events, yearly company trip, end‑of‑year party Hybrid working environment and work‑from‑home setup allowance Clear career progression plan and support English classes MacBook or laptop when you start Social insurance, medical insurance & AON insurance 13th month salary 15 days of annual leave, 30 days of sick leave/mental health, 1 day of occasion leave Support for gym membership Global Fashion Group embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry‑leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non‑discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements. #J-18808-Ljbffr