ERetail Data Science Lead at L'Oreal in New York, NY
This role is responsible for partnering with our team of engineers and analytic experts in the development of best in class performance measurement and predictive modeling solutions that drive day to day success of the business as well as unlock incremental insights that create a competitive advantage. The ideal candidate will have a background in a quantitative field, backed by an experience in working with massive data sets. Should be scrappy, focused on results, a self-starter, and have demonstrated success in using analytics to drive the understanding, growth, and success of the E-Retail business. To succeed the candidate will be backed by extensive experience in working on large multi-source data sets to draw correlations, scaling algorithms to new data sets to drive business solutions and provide insights to cross-functional teams ensuring business strategies are aligned across all initiatives, and leading the implementation of data modeling solutions, among others. Role will be multi-faceted drawing correlations between Operations, Sales, Advertising, and financial data to identify opportunity and create a roadmap for quick wins and for future needs. Overall Responsibilities Support Team via web scraping, data mining and presentation of data to inform the day to day business and product launches (data cleansing, modeling, implementation as needed) Manage product operations (building dashboards and reports) by aggregating data across brands & multiple different reporting systems (ARA, SAP, PDP Information) Exploratory Analysis (building user behavior models, identifying long term trends) to provide Account Managers actionable insights to drive business analysis to improve forecasting, inventory, retailer sell-in, sell-through, inventory management, and various relevant key performance metrics Serve as main point of contact between eCommerce team and both internal and external teams in charge of systems that help run the business like Rakuten, Slice, Clavis, etc. Supply chain and Operations liaison for team both within division specific operations team and cross-divisional E-Retail focused Operations team Identify blue sky opportunities to support the strategic needs and day to day of running the E-Retail business via new capabilities, third party vendors, and other initiatives and build business case for exploration and execution REQUIREMENTS Graduates from data science, engineering, math, statistics, computer science, operations research, supply chain or business analytics background 7-10 years in a strategy & analytics-focused role, working on projects that have enabled them to build strong quantitative skills and business judgment (e.g., management consulting, eCommerce, Operations, Sales Planning or Advanced Analytics) or Advanced degree and at least 1 year of experience in related occupation Experience working with enterprise cloud databases , data analytics, working with large data sets and ideally writing complex SQL/GBQ queries; building complex data analyses by leveraging scripting languages including Python, Java, or a related scripting language; understanding of machine learning and linguistics. Ability to create BigQuery datasets, tables, views and queries Experience working with data visualization tools and creating data visualization concepts. (Excel, Tableau, Microsoft Power Bi, Looker or similar) Prior experience in Beauty, or CPG industries a plus Prior experience with Amazon Vendor Central / Amazon Advertising UI / Walmart Retail Link or related API's from other retailers preferred SAP system experience preferred Clear understanding of relational databases along with a demonstrated ability to merge/transfer text files resulting in the creation of reports from multiple sources Keen sense of detail orientation Experience analyzing performance data and summarizing / communicating findings via reports and presentations Communicates clearly and succinctly in both oral and written forms Ability to work in a fast-paced, deadline-driven environment Proactive and results oriented thinker who would flourish in an entrepreneurial environment where new ideas are championed Must demonstrate strong analytical, critical thinking, and problem-solving skills Highly organized with proven multi-tasking ability Self-motivated and able to work independently.
Salary Range:
$100K -- $150K
Minimum Qualification
Data Science & Machine LearningEstimated Salary: $20 to $28 per hour based on qualifications.
Salary Range:
$100K -- $150K
Minimum Qualification
Data Science & Machine LearningEstimated Salary: $20 to $28 per hour based on qualifications.
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