All job offers Data analyst

Gather, clean, and validate data from various sources, including warehouse management systems (WMS). Perform statistical analysis on large datasets to find insights and present findings. Develop and implement data-driven solutions to streamline warehouse processes. Troubleshoot data inconsistencies and issues within the warehouse and data warehouse systems. Translate business requirements into logical data models and analytical tasks. Assist in developing and managing data warehousing and reporting tool

We are looking for a Data analyst to join our growing AI team at Apparel Group. This role is ideal for someone with a strong foundation in data analytics and machine learning who wants to apply their skills to real-world retail problems. You'll work alongside senior data scientists and product managers on AI-powered solutions such as - from forecasting and workforce optimization to cutting-edge applications of LLMs (Large Language Models) and agentic AI. Key Responsibilities - Assist in building, testing, and deploying machine learning models (forecasting, classification, optimization). - Perform data cleaning, preprocessing, and feature engineering on large structured and unstructured datasets. - Conduct exploratory data analysis (EDA) to discover trends, anomalies, and insights - Work with the team to design and validate experiments, pilots, and predictive models - Support dashboard development and data storytelling for business stakeholders. - Stay updated with new ML/AI techniques (including LLMs and agentic AI) and explore potential use cases. Required Skills & Qualifications - Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Engineering, or related field. - 2+ years of experience in data science or applied machine learning (retail/e-commerce experience preferred). - Strong programming skills in Python (Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn). - Good knowledge of machine learning fundamentals (regression, classification, clustering, time series forecasting). - Experience with SQL and working with relational databases. - Ability to analyze data, communicate insights, and document findings clearly. - Curiosity, eagerness to learn, and ability to work in a fast-paced environment. Preferred Skills (Nice to Have) - Familiarity with deep learning frameworks (TensorFlow, PyTorch). - Exposure to LLMs (Large Language Models) and their applications. - Experience with optimization problems (scheduling, resource allocation). - Knowledge of cloud platforms (Azure, AWS, or GCP). - Hands-on experience with BI tools (Power BI, Tableau)