Senior Inventory Data Analyst at ALO

Beverly Hills, California, United States -

Full Time

Start Date

Immediate

Expiry Date

09 Mar, 26

Salary

115000.0

Posted On

09 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Analytics, Retail Math, Merchandise Planning, SQL, Python, R, BI Tools, Tableau, ThoughtSpot, Predictive Modeling, Statistical Analysis, Data Validation, Dashboard Development, Communication Skills, Problem Solving, Operational Efficiency

Industry

Retail Apparel and Fashion

Description

WHY JOIN ALO? Mindful movement. It’s at the core of why we do what we do at ALO—it’s our calling. Because mindful movement in the studio leads to better living. It changes who yogis are off the mat, making their lives and their communities better. That’s the real meaning of studio-to-street: taking the consciousness from practice on the mat and putting it into practice in life. OVERVIEW The Inventory Data Analyst plays a crucial role in supporting initiatives aimed at continuous improvement in planning and inventory management.This role requires a good understanding of retail and retail math, some merchandise planning or allocation experience is required.This person will collaborate with cross-functional teams to automate existing Excel reports and working with their manager to identify additional opportunities for automation or process improvements. RESPONSIBILITIES Partner with Planning & Allocation, Buying, Finance, and Data Engineering teams to align analytics with business priorities. Build and maintain dashboards, automated reporting, and analytics solutions to democratize data across the organization. Translate complex datasets into actionable insights across sales, inventory and margin that drive growth, improve forecast accuracy, and enhance operational efficiency. Apply predictive modeling and statistical analysis to improve demand planning and inventory allocation decisions. Ensure data accuracy and consistency across systems through validation and quality checks. Establish and uphold best practices in analytics, reporting, and dashboard development, including maintainability and scalability standards. Communicate findings and recommendations to business stakeholders and senior leadership in a clear, impactful manner. QUALIFICATIONS 2–4 years of experience in data analytics, preferably in high-growth e-commerce or digitally enabled retail environments, with proven ability to translate insights into business strategy. Bachelor’s degree in a quantitative field (Economics, Finance, Mathematics, Statistics, Engineering, etc.). Strong SQL skills with experience writing advanced queries (joins, aggregations, CTEs, conditional filters) in analytical data warehouses. Proficiency in Python or R for statistical analysis, data modeling, and automation. Experience with BI tools such as Tableau or ThoughtSpot; capable of building intuitive, scalable dashboards from scratch. Skilled in working with diverse, complex data sources (e.g., Amazon Redshift, Cyberquery, Anaplan, FDM4, Shopify). Excellent communication, prioritization, and problem-solving skills; able to thrive in ambiguous, fast-paced environments. The base salary range for this position is $100,000-$115,000 per year which represents the current range for the base salary for this exempt position. Please note that actual salaries will vary based on factors including but not limited to location, experience, and performance. As such, on occasion and when applicable, there is the possibility that the final, agreed-upon base salary may be outside of the upper end of the range. Please also note the range listed is just one component of the company’s total rewards package for exempt employees. Other rewards may include performance bonuses, long term incentives, a PTO policy, and many other progressive benefits. For CA residents, Job Applicant Privacy Policy HERE.

Responsibilities

The Inventory Data Analyst will partner with various teams to align analytics with business priorities and build automated reporting solutions. They will translate complex datasets into actionable insights to drive growth and improve operational efficiency.