Job Title

About the Company Central to Saks’ customer-centric marketing strategy is our Customer DNA. The successful candidate will be a highly independent and business-savvy Senior Data Scientist to lead the development and execution of advanced analytics that drive measurable business impact. The ideal candidate will demonstrate strong ownership of projects, from framing business problems to delivering actionable recommendations. They will support Saks strategies through the delivery of best-of-breed campaign management, measurement of all-channel and cross banner marketing promotions, the extraction of key analytical insights and by providing customer centric recommendations — spanning both store and e-commerce channels. The ability to think strategically about customer and business challenges and proactively propose solutions will be critical to their success. Forward thinking is the key to this role as new technologies and opportunities present themselves.About the Role Lead the strategic development of data-driven solutions within areas such as business forecasting, product analytics, and targeted marketing. This includes designing and implementing data pipelines, developing analytical frameworks, and creating models that directly influence business decisions.Responsibilities Manage end-to-end data science projects, from defining objectives and scope, to delivering actionable insights and recommendations. Ensure clear communication of project status, findings, and implications to business stakeholders. Contribute to Product DNA data project to support merchandising and buying decisions. Conduct ad-hoc analyses using customer, merchandising, operational, and macroeconomic data to support various Saks initiatives and deliver actionable insights to different functional teams. Develop and automate analytical processes for generating customer profiles, creating targeted campaign lists, and performing post-campaign evaluations. Ensure that insights are actionable and directly applicable to marketing and CRM strategies. Team up with Data Architects, Data Engineers, MLops Engineers, and other company players to conceive and execute data pipelines crucial for our personalization objectives. Stay informed on the latest industry trends and advancements in data science, machine learning, and AI, incorporating new techniques and technologies as appropriate. Drive research and methodology development for machine learning use cases in product recommendation, customer journey optimization, and conversion enhancement. Gather business requirements for critical blind spots in business processes such as access to customer information, and design an application that is marketer-friendly but solves data gaps and consumes data science models for end-user applications.Qualifications 5+ years of demonstrated ability in a similar data scientist role. Bachelor’s degree in data science, computer science, statistics, economics, mathematics, or a similar quantitative field; Master’s Degree preferred.Required Skills Comprehensive experience with ML and AI modeling, especially in product recommendation algorithms and NLP. Proven track record of teaming up with data engineers for large-scale ML tool production. Proficient programming skills in relevant languages/tools (Python, SQL, Spark, Git & Github, AWS EMR, Airflow, AWS SageMaker, Dataiku, or similar platforms). Ability to apply the ML/AI modeling approaches/classes of algorithms to business problems e.g., regressions, Random Forest, GBM, Neural Networks, boosted trees, LDA, collaborative filtering, etc. Strong business acumen and knowledge of retail business and digital marketing. Excellent communication skills and value in building solid relationships cross-functionally to capture business needs and translate them into actionable project plans to influence real-world marketing applications or decisions.Preferred Skills Python, SQL, AWS, Pyspark, Advanced Deep Learning.