Sr Analyst - Pricing Data Science

Sr Analyst - Pricing Data Science

The Sr Analyst - Pricing Data Science will be responsible for the development and deployment of quantitative models related to pricing, promotions, and clearance. We firmly believe that the strategic use of deep analytics is critical to driving competitive advantage, disciplined decision-making, and enhanced profitability in the modern retail domain. To this end, this team member will strive to deliver best-in-class decision support through adoption of modern predictive frameworks, including machine learning algorithms, alongside traditional analytic techniques deployed to transform data into execution-ready strategies.

Major Activities : Data Mining, Model Building, Reporting

• Work with large scale and complex traditional and non-traditional data sources to identify opportunities that enhance performance and efficiency of discounting and base pricing.
• Demonstrate strong expertise in leveraging quantitative tools and approaches to transforming raw data into insights, such as data mining, dimension reduction, segmentation, response modeling, and designing of experiments.
• Develop advanced algorithms to derive insights and make recommendations for optimizing business results in pricing.
• Ensure that the data used for algorithms / model development is reliable and robust and that it adheres to industry standards. Leading the preparation and management of complex data is essential for ensuring model integrity. Strong understanding of business-related characteristics, as well as proper handling of data anomalies and missing values are critical success factors.

Model Monitoring and Reporting

Business Insights & Cross Functional Partnerships

Minimum Education : Bachelor's degree in a relevant quantitative field required.

Minimum Special Certifications or Technical Skills : Fluent in data fundamentals : SQL, data manipulation using a procedural language (R, Python), statistics, experimentation, and modeling.

Minimum Type of Experience the Job Requires : A minimum of 1-2 years of relevant work experience in decision sciences. Demonstrated skill in communicating complex analysis to non-experts. Expert-level experience with a wide range of quantitative methods that can be applied to business problems. This includes knowledge of modeling techniques and statistical concepts.

Preferred Education : Advanced degree preferred in analytical field (e.g. Statistics, Economics, Applied Math, Operations Research, Physics, Data Science fields); MS in a quantitative field preferred.