SAS

As a Lead Data Analyst you will play a crucial role in driving data-driven decision-making processes within our organization. You will leverage your expertise in data analysis and statistical techniques to provide insights that enhance business performance. This role requires a strong technical background in various data analysis tools and a keen understanding of retail demand forecasting.

Responsibilities

• Lead the analysis of complex data sets to identify trends and patterns that inform business strategies.
• Oversee the development and implementation of data models using SAS and R Statistical Package.
• Provide insights through exploratory data analysis to support decision-making processes.
• Utilize LS Salesforce and Dataiku to streamline data workflows and enhance data accessibility.
• Conduct incentive compensation management analysis to optimize sales performance.
• Apply machine learning techniques to improve predictive accuracy in demand forecasting.
• Calculate ROI to assess the effectiveness of business initiatives and strategies.
• Employ Alteryx for data preparation and blending to ensure data quality and consistency.
• Develop and maintain SQL scripts for data extraction and manipulation.
• Use Python for advanced data analysis and automation of repetitive tasks.
• Create comprehensive reports and presentations using MS Excel and MS PowerPoint to communicate findings to stakeholders.
• Collaborate with cross-functional teams to align data analysis efforts with business objectives.
• Ensure data integrity and security in all analytical processes. Qualifications
• Possess a strong technical background with mandatory skills in SAS LS Salesforce Statistics EDA Incentive Compensation Management Dataiku Machine Learning ROI Calculation Alteryx Retail Demand Forecasting R Statistical Package MS Excel Python SQL Scripting and MS PowerPoint.
• Demonstrate excellent analytical and problem-solving skills with a focus on actionable insights.
• Exhibit proficiency in English for effective communication and collaboration.
• Have domain experience in Finance & Accounting as a nice-to-have skill.
• Show ability to work in a hybrid model with a focus on day shifts.
• Display strong organizational skills and attention to detail in managing data projects.