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Senior Data Scientist - Retail

Burlington Stores, Inc. United State
Relocation
This Job is No Longer Active This position is no longer accepting applications

Job Description


Position Overview

Come join our growing team here at Burlington Stores as a Data Scientist II! The Data Scientist II will support business areas including Allocations, Inventory and Supply Chain Analytics teams with insights gained from analyzing Burlington and external data. Must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools building and implementing models, using/creating algorithms and creating/running simulations. Must have strong interpersonal and relationship building skills & strong written and verbal communication skills.

Retail Operations with Supply Chain and Inventory datasets experience is required.

This is a hybrid role requiring every other week (Wednesday/Thursday). Relocation can be considered.

A Day In The Life

  • Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions
  • Mine and analyze data from the data warehouse to drive optimization and improvement of product allocation, marketing strategy and drive sales
  • Develop predictive models using various algorithms and come up with the best outcomes for business to follow
  • Keep up-to-date with latest technology trends
  • Coordinate with different functional teams to implement models and monitor outcomes
  • Develop processes and tools to monitor and analyze model performance and data accuracy
  • Create presentation of gained insights and explain it to stakeholders

You'll Come With

  • Bachelors/Masters Degree or a Foreign Equivalent
  • 5+ years Data Science experience with extensive background in building ML models, data mining and statistical analysis
  • 5+ years experience in coding using Python/PySpark or equivalent
  • Experience utilizing Databricks and Snowflake
  • Proven experience applying machine learning algorithms (e.g., supervised and unsupervised learning, deep learning) and optimization models to real-world business problems, including model development, optimization, and deployment in production environments
  • 3+ years Experience in building retail operations ML models (e.g. Demand Forecasting, Inventory Allocation, Carton Forecasting, etc.) at different store product mapping levels (e.g. at store-SKU, store-Division models etc.)
  • Practical experience with Snowflake, SaaS, Netezza, data processing, database programming and data analytics is a plus
  • Experience in writing SQL code to access data from the data warehouse
  • Able to understand various data structures and common methods in data transformation
  • Excellent pattern recognition and predictive modeling skills
  • Working knowledge with Analytical tools like Power BI, MicroStrategy, Tableau, Looker, etc.
  • Experience in presenting end-to-end models/results for different stakeholders in the company

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Come join our team. You’re going to like it here!

You will enjoy competitive wages, flexible hours, and an associate discount. Burlington’s benefits package includes medical, dental and vision coverage including life and disability insurance. Full-time associates are also eligible for paid time off, paid holidays and a 401(k) plan. We are a rapidly growing brand and provide a variety of training and development opportunities so our associates can grow with us. Our teams work hard and have fun together! Burlington associates make a difference in the lives of customers, colleagues, and the communities where we live and work every day. Burlington Stores, Inc. is an equal opportunity employer committed to workplace diversity.

Individual pay decisions will be based on a variety of factors, such as but not limited to, qualifications, education, job-related skills, relevant experience, and geographic location.

Min-Mid $115,000.00 - $150,000.00

Posting Number 2025-228794

Location New Jersey-Edgewater Park

Address 4287 Route 130 S

Zip Code 08010

Pay Rate Salaried

Career Site Category Corporate

Position Category Information Technology

Job Type Full-Time

Remote Type Hybrid

Evergreen No


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