Data Scientist – Personalization & Search İş İlanı

Are You Ready to Join LC Waikiki’s Digital Transformation Journey? 🚀 With over e-commerce operations in 14 countries, 1300 stores worldwide and a strong presence in 60 countries, we embark on a great journey embracing the philosophy that 'Everyone Deserves to Dress Well.' Beyond the world of fashion, we are also pursuing significant goals in technology and digital transformation. At LC Waikiki’s Digital Transformation and IT Department, we’re shaping the future with over 850 experts, focusing on innovation and collaboration. Using Agile/Scrum methodologies, we strive to become a more efficient and dynamic team every day. 🚀 We are looking for Mid/Senior Data Scientist – Personalization & Search What We Offer: Our projects touch not only the retail world but also every corner of the digital realm. If you're excited to be part of this journey, here are the opportunities awaiting you: Personalization, Search and Recommendation Systems Design and develop recommendation systems using collaborative filtering, content-based filtering, hybrid recommendation approaches, and deep learning-based retrieval architectures. Build and optimize personalized ranking models for product recommendations, search result ranking, and merchandising use cases. Develop retrieval systems leveraging dense, sparse, and hybrid retrieval techniques. Implement and improve search relevance using semantic search, vector search, and multimodal retrieval approaches. Design recommendation pipelines including candidate generation, retrieval, ranking, re-ranking, diversification, and business-rule optimization stages. Apply association rule mining and frequently-bought-together techniques to discover product affinities and improve cross-sell and upsell experiences. Fashion AI and Multimodal Intelligence Develop machine learning solutions utilizing text, image, and behavioral signals to improve personalization and product discovery experiences. Work with multimodal embedding models such as FashionCLIP, FashionSigLIP, CLIP, SigLIP, and similar architectures for fashion understanding tasks. Build semantic similarity systems for product matching, visual search, outfit recommendation, and catalog enrichment. Explore emerging multimodal AI techniques to enhance customer engagement and product discoverability. Stakeholder Management Act as a key partner for business stakeholders on personalization and search initiatives. Translate complex machine learning concepts into actionable business recommendations. Communicate model performance, experimentation results, and business impact to technical and non-technical audiences. Present findings and recommendations to senior leadership and product teams. Innovation and Research Stay up to date with advancements in recommendation systems, search technologies, deep learning, and Generative AI. Evaluate and prototype emerging methodologies, architectures, and tools to improve personalization capabilities. Contribute to innovation initiatives by identifying and testing new opportunities in AI-driven customer experiences. Who Are We Looking For? We're looking for a passionate and innovative Mid/Senior Data Scientist who enjoys building intelligent personalization, recommendation, and search systems that directly impact customer experiences. Required Qualifications Minimum of 2 years of experience in Data Science, Machine Learning, Personalization, Recommendation Systems, Search, or related domains. Strong proficiency in Python and modern machine learning development practices. Strong understanding of supervised learning algorithms, particularly tree-based methods such as LightGBM, XGBoost, CatBoost, and Random Forests. Hands-on experience designing, training, tuning, and deploying deep neural network architectures, including retrieval and ranking models for personalization use cases. Experience with TensorFlow, TensorFlow Recommenders (TFRS), PyTorch, or similar deep learning frameworks. Comprehensive understanding of recommendation system methodologies including: Collaborative Filtering Content-Based Filtering Hybrid Recommendation Systems Matrix Factorization Two-Tower Retrieval Models Learning-to-Rank Approaches Experience with product affinity and market basket analysis techniques including: Apriori FP-Growth Association Rule Mining Frequently Bought Together Systems Strong understanding of retrieval architectures including: Dense Retrieval Sparse Retrieval Hybrid Retrieval Semantic Search Vector Search Good understanding of embedding technologies and multimodal representation learning, particularly within the fashion domain. Experience with multimodal embedding models such as FashionCLIP, FashionSigLIP, CLIP, SigLIP, or equivalent architectures. Experience working with vector databases and ANN search technologies such as FAISS, Milvus, Vertex AI Vector Search, Azure AI Search, Pinecone, Weaviate, or similar platforms. Proficiency in cloud environments such as Google Cloud Platform and Microsoft Azure. Experience deploying machine learning and recommendation solutions through batch and real-time serving architectures. Understanding of MLOps concepts including model versioning, monitoring, experimentation tracking, and CI/CD workflows. Strong SQL skills and experience working with large-scale datasets. Excellent analytical, problem-solving, and communication skills. Preferred Qualifications Experience building large-scale recommendation systems in retail, e-commerce, marketplaces, media, or consumer-facing products. Experience with ranking models such as LightGBM Ranker, XGBoost Ranker, LambdaMART, or neural ranking architectures. Experience with A/B testing frameworks and online experimentation methodologies. Experience with feature stores, real-time feature engineering, and recommendation serving infrastructures. Familiarity with Generative AI applications for search, personalization, product discovery, or shopping assistants. Experience working with fashion, retail, apparel, or lifestyle-related machine learning applications. What’s Waiting for You: Hybrid Work Option: At our modern office in Giyimkent, Istanbul. A team culture focused on collaboration and inclusivity. The chance to work with cutting-edge technology and tools. Ongoing training and professional development opportunities. Discounts on LC Waikiki products and much more! Join Us! We’re excited to meet software developers who want to leave their mark in the digital world while helping us achieve our big goals. If this opportunity excites you, apply now and become part of our digital transformation journey! At LC Waikiki, we are committed to considering our environmental and social impacts throughout our value chain while developing and maintaining an ethical, responsible, and sustainable business model that respects human rights. The person in this role is expected to consider not only the balance between cost, quality, and speed in decisions and practices within their area of responsibility and influence, but also resource efficiency, the use of sustainable materials, responsible production and procurement practices, respect for human rights, decent working conditions, and ethical business principles. In addition, they are expected to contribute to the identification, management, and monitoring of relevant sustainability impacts, risks, and opportunities. Hiring Process: Application Interview / Vibe Coding Assessment Center Activities Reference Check Offer (Varies by position)