Data Science Manager

2 months ago

Bangalore City, India Saks India Full time
Manager, Data ScienceSaks is a world-renowned luxury ecommerce destination. The company’s unique approach combines a focus on the digital customer experience with a strong connection to a network of extraordinary stores that extends that seamless experience into the real world. On its website and app, Saks offers an unparalleled selection of curated merchandise across fashion for women and men, beauty, jewelry, home décor and more. In addition to the shopping experience, customers come to Saks for inspiring editorial content, access to digital stylists, lifestyle experiences and other world-class services. The company is currently in the midst of a dramatic expansion, driven by significant enhancements to its platforms and offerings, with the goal of becoming the preeminent destination for luxury internationally.Responsibilities Lead and manage the analytics and data science teams at Saks.Ability to motivate others and have ownership over individuals output, and people retention.Manage relationships between India and US based team members, making sure collaboration is seamless and productivity is high.Understand and guide development in a wide variety of analytical fields such as;

marketing measurement models, segmentation, personalization, pricing, markdown optimization, forecasting and causal inference.Ability to be flexible and 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.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:8-12yrs of experience working with a team and leaders in the US, as well as strong communication and collaboration skills.Ability to take direction with limited communication/overlap with US based teams.A master's or Ph.D. degree in a quantitative field such as Data Science, Statistics, Computer Science, or a related field.Proven experience (5+ 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,Expertise solving complex optimization problems.Experience in retail, and complex large organizations.Excellent proficiency in Python and SQL.Your Life and Career at Saks:Be part of an empowered, innovative team;

work with an adventurous spirit and a customer-centric mindset;

play a critical role inmaking decisions that will position us to winExposure to rewarding career advancement opportunities across different functions within our corporate offices, retail stores, photo studios, and distribution centersA culture that promotes a flexible work environmentAttractive benefits package for all eligible employees and other exciting perksSaks provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Saks complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.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.Thank you for your interest with Saks. We look forward to reviewing your application.

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