Data Scientist Job at Apparel Group

Job Description

Key Responsibilities

Business-Centric AI & Modeling

• Partner with internal stakeholders (Brand Marketing, Merchandising, CRM, and Business Strategy teams) to identify opportunities to apply ML, LLMs, and agent-based intelligence for high-value retail use cases.

• Design, develop, and deploy advanced Demand Forecasting, Markdown Optimization, and Price Elasticity models to optimize inventory and pricing strategy.

• Build and operationalize Customer Lifetime Value (CLTV), Churn Prediction, and RFM segmentation models for personalized marketing and retention strategy.

• Develop Market Basket Analysis, Cross-Sell/Recommender Systems, and Promotion Effectiveness frameworks using both classical ML and deep learning approaches.

• Create and maintain Agentic AI workflows for campaign orchestration, customer service automation, and marketing optimization (e.g., autonomous agents for A/B test selection or personalized product recommendations).

Advanced AI & Generative Intelligence

• Fine-tune Small and Large Language Models (e.g., LLaMA, Mistral, GPT, Claude) for tasks such as customer sentiment analysis, product description enrichment, and insight summarization.

• Design retrieval-augmented generation (RAG) pipelines integrating structured and unstructured data (CRM, catalog, social, and web data).

• Experiment with Agentic AI frameworks (LangChain, CrewAI, AutoGen, OpenDevin, etc.) to build multi-agent systems that can autonomously gather insights, recommend actions, or run simulations.

• Apply multimodal models (text + image) for fashion tagging, trend analysis, and visual recommendation.

MLOps, Engineering, and Deployment

• Partner with the Data Engineering and MLOps teams to productionize models at scale via CI/CD pipelines.

• Develop scalable APIs and deploy models into cloud environments (Azure, AWS, or GCP).

• Build robust monitoring frameworks for model drift, bias detection, and performance tracking.

• Contribute to development of internal AI/ML model registry and experimentation frameworks.

Qualifications

Core Data Science & ML

• 3–5 years of experience in applied data science, ideally within retail or e-commerce sectors.

• Expertise in supervised, unsupervised, and deep learning techniques (Regression, Random Forest, XGBoost, LightGBM, ARIMA, SARIMAX, GARCH, CNNs, RNNs, Transformers, etc.).

• Strong experience with time series forecasting, optimization modeling, and causal inference.

• Experience with feature engineering, model tuning, and validation at scale.

LLM, SLM & Agentic AI Exposure

• Experience fine-tuning or prompt-engineering LLMs for enterprise tasks (e.g., summarization, insight generation, or dialogue systems).

• Familiarity with LangChain, LlamaIndex, or CrewAI for developing autonomous or semi-autonomous agents.

• Understanding of retrieval-augmented generation (RAG), vector databases (FAISS, Pinecone, Weaviate), and embedding models.

• Experience leveraging multimodal AI (vision + language) for product recommendations or catalog enrichment.

Programming & Tools

• Advanced proficiency in Python, PySpark, and SQL.

• Experience with TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, and LLM APIs.

• Exposure to any of the MLOps frameworks (MLflow, Kubeflow, Airflow, Vertex AI, SageMaker).

• Comfortable with distributed computing tools (Spark, Hadoop, Hive) and data lakes (Databricks, Delta Lake).

Business & Communication

• Proven ability to translate complex data insights into business strategy.

• Experience collaborating with non-technical stakeholders in retail, marketing, and merchandising domains.

• Excellent written and verbal communication skills.

Preferred

• Master’s or PhD in Statistics, Computer Science, Applied Mathematics, or related field.

• Exposure to fashion retail analytics, customer behavior modeling, and omnichannel data systems.

• Familiarity with Web Analytics tools (Google Analytics, Adobe Analytics) and APIs (Google Maps, Geocoding, etc.).

Why Join Us

• Shape the future of AI-led decisioning in one of the region’s largest fashion retail conglomerates.

• Work on real-world generative and agentic AI projects beyond prototypes.

• Be part of a collaborative, innovative, and impact-driven Data Science & AI team.