Senior Data Analyst at SKIMS focused on enhancing data-driven strategies for global growth. Partnering with key business functions to provide actionable insights and optimize analytics processes.
Responsibilities
Partner with a dedicated business function as the primary analytics contact, owning analytical deliverables and translating business questions into clear, data-driven recommendations.
Build and maintain reusable analytical frameworks, scripts, and tools in Python or SQL to automate recurring analyses, improve data access, and scale the team’s capabilities.
Apply statistical and predictive modeling techniques to uncover patterns, forecast outcomes, and support decisions around areas such as customer lifetime value, demand planning, and resource allocation.
Identify opportunities for optimization, customer segmentation, and targeting across the supported business function by providing stakeholders with actionable insight into customer preferences, behaviors, and trends.
Design and execute experiments, including A/B tests, to measure the impact of business initiatives and communicate results and recommendations clearly to stakeholders.
Evaluate and validate analytical models using appropriate statistical performance metrics to ensure accuracy and reliability. Develop analytics roadmaps in partnership with business stakeholders, aligning data initiatives to functional goals and translating trend analysis into actionable forecasts.
Partner with data engineering and technology teams to define data requirements, ensure data quality, and build robust pipelines that support reliable, scalable analytics across the organization.
Create executive-level dashboards using visualization tools like Looker, Tableau, or PowerBI that empower self-service, data-driven decision making.
Build strong relationships with business stakeholders, proactively identifying analytical needs, communicating findings in clear and compelling ways, and influencing decisions at the leadership level.
Serve as a resource and informal mentor to junior team members, sharing expertise in analytical methods, data best practices, and stakeholder communication to continuously elevate the team’s capabilities.
Requirements
Bachelor’s degree in Statistics, Data Science, or a related field and 5+ years of experience in a senior analytics role. Prior experience in the ecommerce or retail industry (e.g., DTC apparel, fashion, or consumer goods) is a plus.
Accessing, transforming, and modeling large datasets using SQL and Python to surface patterns, trends, and actionable insights, including experience applying predictive and statistical models to business problems.
Querying and manipulating large datasets using BI and analytics tools (e.g., Snowflake, SQL, Python, Looker), with strong command of data wrangling, transformation, and exploratory analysis. Designing and measuring experiments, including A/B tests, to evaluate business initiatives.
Creating executive-level dashboards using visualization tools like Looker, Tableau, or PowerBI.
Leading end-to-end analytics projects with minimal oversight, defining measurement frameworks and translating ambiguous business questions into structured analytical plans.
Benefits
Up to 100% Company Paid Healthcare (medical, dental, vision)
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