Data Analyst

Data Analyst Overview

• The Data Analyst role focuses on building data pipelines and applying machine learning techniques to analyze and model datasets.
• Collaborate with IT and data teams to support business stakeholders in sales, merchandising, and supply chain operations.
• Utilize Python and AI tools to extract insights from ERP and DTC data for decision-making.
• Work in a hybrid environment, combining remote flexibility with on-site collaboration.
• Gain exposure to advanced analytics platforms like Snowflake and Power BI for reporting and visualization.
• Opportunity to work with cutting-edge AI tools and machine learning applications.
• Engage in data governance practices to ensure security, quality, and documentation standards.
• Ideal for professionals with a passion for data science and a curiosity for AI-driven business solutions.

Data Analyst Key Responsibilities & Duties

• Design, build, and maintain ETL/ELT pipelines for data integration from diverse sources into Snowflake.
• Apply machine learning techniques for demand forecasting, customer segmentation, and anomaly detection.
• Develop Python scripts to automate data acquisition and processing tasks.
• Navigate ERP and PLM databases to map tables, joins, and business keys effectively.
• Leverage AI tools to enhance coding, documentation, and prototype development for analytics use cases.
• Transform analysis into actionable insights and visual reports for business stakeholders.
• Ensure compliance with data governance standards, including security, access, and quality protocols.
• Collaborate with cross-functional teams to align data strategies with organizational goals.

Data Analyst Job Requirements

• Bachelor's degree in Data Science, Computer Science, Statistics, or related field.
• Minimum of 3 years' experience in data analysis or engineering; 5 years preferred.
• Proficiency in Python for data manipulation and SQL for relational database management.
• Knowledge of machine learning techniques and their practical applications in business contexts.
• Experience with Snowflake, Power BI, and integration tools like Azure Data Factory.
• Familiarity with wholesale, fashion, or apparel industry data structures is advantageous.
• Strong analytical mindset and ability to communicate findings to non-technical audiences.
• Commitment to data governance, documentation, and security best practices.