Sr Analyst, Business Intelligence
Acosta · Chesterfield, MO · 1 mo ago
$62k–$70k/yrFull-time
About the role
This is a #Hybrid role, requiring 3 days in the office per week. You will perform a valuable role in support of the sales team and build a strong partnership with our clients. You will conduct high-quality analysis and synthesis of multi-source data to evaluate item performance, assortment planning, and store clustering through the modular process, while leveraging effective communication & influencing to orchestrate action.
Responsibilities
- Provide analytical analysis, insights, and recommendations for category management projects and initiatives utilizing retailer POS and NielsenIQ/Circana (IRI) data sources and reporting tools.
- System tools required: Retailer POS, Circana (IRI)/NielsenIQ
- Strong analytics, insights, presentation, and storytelling skills
- Participate in the development of category presentations incorporating syndicated data and other sources of data that address business issues
- Work closely with CPG Category Management and Space Technology teams to ensure quality results are delivered
- Keep abreast of client's KPIs, strategies, innovation, and other important information.
- Leverage relationships with clients to understand key retailer deliverables, category strategies, and project timelines.
- Category Analyst/Manager Certification is a plus.
Qualifications
- Education Requirements: Bachelor's Degree (Related work experience may be substituted for the educational requirement)
- Work Experience Requirements: 2+ years related experience
- Knowledge, Skills, and Abilities Requirements:
- Demonstrate an advanced degree of proficiency in Windows and related software applications, including Excel, PowerPoint, VB, and advanced macros.
- Experience with syndicated data and/or space management tools.
- Clearly and concisely communicate relevant information.
- Identify and leverage relevant data to diagnose situations and identify potential solutions
- Effectively and independently conduct data mining utilizing CPG math concepts and tools.