Saks Fifth Avenue OFF 5TH
Senior Data Scientist
Saks Fifth Avenue OFF 5TH, Indiana, Pennsylvania, us, 15705
Saks OFF 5TH
is the premier luxury off-price destination. In its more than 100 stores in the U.S. and Canada, and online, at SaksOFF5TH.com, the company provides the best names in fashion at an incredible value through its merchandise authority, unparalleled brand access and seamless connection between ecommerce and stores.
What This Position Is All About:Lead the development and implementation of our segmentation, personalization and other personalized strategies.Partner closely with our Loyalty team to ensure our program maximizes a customer's LTV with Saks Off 5th.Build strong relationships with our acquisition and retention teams and leaders, becoming a part of their daily work.Utilize statistical and machine learning techniques to analyze large datasets and extract meaningful insights for project and ad hoc requests.Develop, validate, and deploy predictive models and algorithms to solve complex business problems.Establish a seamless connection between our customer strategy and merchandising strategy by analyzing customer behavior and preferences.Manage and/or mentor a team of data scientists, fostering their professional growth and ensuring high-quality work.Collaborate with other departments and stakeholders to align data science projects with organizational objectives.Stay updated on the latest data science and retail industry trends, ensuring that the team remains at the forefront of technology and methodology.Who Are You:A master's degree in a quantitative field such as Data Science, Statistics, Computer Science, or a related field.Proven experience (3+ years) in leading or working with data science teams.Experience with a variety of ML frameworks and libraries (e.g., pandas, numpy, pytorch, xgboost, econ-ml, seaborn, scikit-learn, keras, theano).Strong expertise in segmentation, customer affinity, and personalization.Expertise solving complex optimization problems.Some experience in retail merchandising analytics.Excellent proficiency in Python and SQL.Strong communication and collaboration skills.Your Life and Career at Saks OFF 5TH:Be part of an empowered, innovative team; work with an adventurous spirit and a customer-centric mindset; play a critical role in making decisions that will position us to win.Exposure to rewarding career advancement opportunities across different functions within our corporate offices, retail stores, photo studios, and distribution centers.A culture that promotes a flexible work environment.Benefits package for all eligible full-time employees (including medical, dental and vision).An amazing employee discount and other exciting perks.Thank you for your interest with Saks OFF 5TH. We look forward to reviewing your application.We believe that our differences not only make us stronger, but also guide our evolution and future growth. All associates are expected to create an inclusive environment free from harassment, discrimination, and bullying. Together, we celebrate, advocate for, and learn from our colleagues, customers and communities to create the best environment to shop and work for all.
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is the premier luxury off-price destination. In its more than 100 stores in the U.S. and Canada, and online, at SaksOFF5TH.com, the company provides the best names in fashion at an incredible value through its merchandise authority, unparalleled brand access and seamless connection between ecommerce and stores.
What This Position Is All About:Lead the development and implementation of our segmentation, personalization and other personalized strategies.Partner closely with our Loyalty team to ensure our program maximizes a customer's LTV with Saks Off 5th.Build strong relationships with our acquisition and retention teams and leaders, becoming a part of their daily work.Utilize statistical and machine learning techniques to analyze large datasets and extract meaningful insights for project and ad hoc requests.Develop, validate, and deploy predictive models and algorithms to solve complex business problems.Establish a seamless connection between our customer strategy and merchandising strategy by analyzing customer behavior and preferences.Manage and/or mentor a team of data scientists, fostering their professional growth and ensuring high-quality work.Collaborate with other departments and stakeholders to align data science projects with organizational objectives.Stay updated on the latest data science and retail industry trends, ensuring that the team remains at the forefront of technology and methodology.Who Are You:A master's degree in a quantitative field such as Data Science, Statistics, Computer Science, or a related field.Proven experience (3+ years) in leading or working with data science teams.Experience with a variety of ML frameworks and libraries (e.g., pandas, numpy, pytorch, xgboost, econ-ml, seaborn, scikit-learn, keras, theano).Strong expertise in segmentation, customer affinity, and personalization.Expertise solving complex optimization problems.Some experience in retail merchandising analytics.Excellent proficiency in Python and SQL.Strong communication and collaboration skills.Your Life and Career at Saks OFF 5TH:Be part of an empowered, innovative team; work with an adventurous spirit and a customer-centric mindset; play a critical role in making decisions that will position us to win.Exposure to rewarding career advancement opportunities across different functions within our corporate offices, retail stores, photo studios, and distribution centers.A culture that promotes a flexible work environment.Benefits package for all eligible full-time employees (including medical, dental and vision).An amazing employee discount and other exciting perks.Thank you for your interest with Saks OFF 5TH. We look forward to reviewing your application.We believe that our differences not only make us stronger, but also guide our evolution and future growth. All associates are expected to create an inclusive environment free from harassment, discrimination, and bullying. Together, we celebrate, advocate for, and learn from our colleagues, customers and communities to create the best environment to shop and work for all.
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