Data Scientist Lead
On-siteLong Island City, New York, United States
Job Summary
Design, develop, and implement advanced data science models for priority business use cases across the enterprise, including online experience, marketing, merchandising, supply chain, and store operations. Lead research initiatives into state-of-the-art methodologies to enhance current models and power future personalized AI-enabled services. Collaborate with business stakeholders to define requirements, KPIs, and acceptance criteria, while working with data engineers and ML engineers to build real-time and batch machine learning pipelines. Monitor, coach, and motivate teammates to promote efficacy through data-driven decision-making and A/B testing evaluation.
Required Qualifications
- Master's degree
- SQL and Python experience
- Blend of applied math, data science and engineering skills
- proven track record of solving critical business problems through data science
- strong analytical/quantitative and engineering skills
- Ability to think creatively, strategically, and technically to identify data issues and take actions to remediate
- Experience in leveraging data cleaning, transformation, analytics and reporting from large data sets to support use cases and drive business value
- Demonstrated leadership skills
- Excellent communication skills, especially when it comes to requirements gathering, communicating with stakeholders, and summarizing and presenting analysis
Desired Qualifications
- Ph. D.
- engineering, business, finance, data science, computer science, or other relevant fields of study
- Familiarity with visualization tools such as Tableau, Power BI or Looker
- Experience with web reporting tools like Adobe Analytics or Google Analytics
- Ability to conduct qualitative market research and perform qualitative analysis, identify trends and patterns in the data and tell a compelling story through visualization and presentation
- Experience with Cloud (GCP, Azure, AWS) and big data processing technologies (Redshift, Big Query)
- Ability to collaborate and work closely with cross-functional teams - Data Scientists, Data Engineers, Data Analysts, business and solution architects and partners
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