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.
