Position Overview
As a Senior Data Scientist, you will support business areas including Merchandising, Allocations, Marketing, IT and Supply Chain Analytics teams with insights gained from analyzing Burlington and external data. Must have experience in applying retail operation machine learning algorithms (e.g. Supply Chain, Demand Forecasting, Inventory Allocation, Carton Forecasting, etc) and optimization models to real-world business problems, including model development, optimization, and deployment in production environments. Must have strong interpersonal and relationship building skills & strong written and verbal communication skills. Burlington is committed to being an employer of choice. We offer a competitive wage and benefit package including a generous paid time off plan, a company matched 401(k) and an associate discount. Our associates make a difference in the lives of customers, colleagues, and our communities through various social responsibility initiatives. As a growing company, we offer a variety of professional development and career growth opportunities.
A Day In The Life
Work with stakeholders throughout the organization including Merchandising, Allocations, Marketing, IT and Supply Chain Analytics 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, transportation and logistics 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
Translate complex analytical findings into clear business recommendations
You'll Come With
7+ years of experience in ETL, data mining, statistical analysis, and building ML models.
Advanced US 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
5+ years practical experience with Snowflake, SaaS, NetezzL, data processing, database programming and data analytics
Experience in time series forecasting
Experience in writing SQL code to access data from the data warehouse
Able to understand various data structures and common methods in data transformation
Familiarity with supply chain systems
Excellent pattern recognition and predictive modeling skills
Knowledge of optimization algorithms
Knowledge with Analytical/Visualization tools like Power BI, MicroStrategy, Tableau, Looker, etc
Knowledge of automation tools to schedule jobs
Good to have retail experience
Experience in presenting end-to-end models/results for different stakeholders in the company
LI-TG1
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 $95,000.00 - $125,000.00
Posting Number R102130
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
