A well-known apparel brand is seeking a Senior Data Analyst , to be responsible for turning complex data into actionable strategies across the organization. You will master the full analytics lifecycle : from designing executive-ready data visualizations to build / productionize robust Machine Learning (ML) models. If you have a passion for the e-commerce space, this is a phenomenal opportunity to drive tangible, data-driven results on a fast-growing business.
Location : Beverly Hills, CA
Salary : Up to 200k total
Responsibilities :
- Independently execute complex, deep-dive exploratory data analysis to proactively identify non-obvious, actionable insights and significant trends that directly influence business strategy and investment.
- Design, build, and maintain a standardized suite of interactive dashboards and executive-level reports, utilizing advanced visualization techniques to effectively communicate data narratives to senior stakeholders.
- Own the end-to-end development, deployment, and performance monitoring of ML models designed to solve critical business challenges (e.g., forecasting, recommendation engines).
- Drive innovation by proactively researching, experimenting with, and building proofs-of-concept for how AI can solve business problems.
- Scope, conduct, and deliver comprehensive ad-hoc analysis for the most ambiguous business questions, providing clear, well-supported conclusions and strategic recommendations.
- Continuously evaluate and optimize existing data processes, tooling, and methodologies to enhance the speed and quality of analytical output.
Requirements :
3+ years of experience in a Data Analyst or similar quantitative role.Bachelor's or Master's degree in a quantitative field (e.g., Applied Statistics, Mathematics, Data Science, Computer Science, Economics).Expert-level analytical, critical thinking, and structured problem-solving skills, with a proven ability to handle ambiguous and unstructured problems.Advanced proficiency in SQL, including deep experience writing highly complex queries, tuning query performance, and implementing robust data quality checks.Strong programming skills in Python with practical experience utilizing libraries for data manipulation (e.g., Pandas), statistics, and ML (e.g., Scikit-learn, TensorFlow, PyTorch).Proven expertise with data visualization tools such as Looker, Tableau, or PowerBIExperience with Snowflake (AWS, or GCP)Deep understanding and practical application of statistical concepts (e.g., hypothesis testing, regression analysis, experimental design, A / B testing).Proven experience with the full Machine Learning lifecycle, including feature engineering, model selection, hyperparameter tuning, cross-validation, and production deployment