Staff Data Scientist, Weee!

• MS in Math, Statistics, or another closely-related quantitative field
• 8+ years of Data Analysis experience in data science or analytics with a proven record of applying advanced analytical methods to drive growth, preferably in e-commerce or customer-facing industry
• Demonstrates proficiency in statistical modeling, machine learning and deep learning modeling
• Architect scalable dashboards, self-serve tools and pipelines that enable all levels of the business to access trusted, consistent data. Create visualizations using, e.g., Tableau, PowerBI (or similar BI tools) to communicate insights
• Advanced skills in SQL, Python, R and other analytical tools
• Able to work with multiple stakeholders and cross collaborate with different business units to quickly understand the business needs
• Serve as a technical subject matter expert in analytics; strong statistical reasoning skills, experimental design and applied machine learning skills
• Raise the analytics bar by mentoring other Data Scientists and Analysts, establishing best practices in experimentation, modeling and story telling
• Exceptional problem-solving skills
• Ability to work in a fast-paced start-up environment and deliver excellent results, requiring minimal supervision

Desirable

• We’re looking for a Staff Data Scientist with a passion for working with pricing, marketing, finance, merchandising, and user behavioral data to help define strategy, guide operations, and KPIs
• As a Staff Data Scientist, you will operate as a senior individual contributor, partnering closely with peers and leaders to identify, validate and refine the growth strategies
• Build dashboards, self-service tools, and ad hoc reports to analyze and present data associated with customer experience, business operations, and strategic decision making
• Work closely with the Product team to test, craft, and measure product experiences and identify trends and opportunities
• Conduct end-to-end analyses, including data gathering from large and complex data sets, processing, and analysis employing advanced statistical and ML methods, with ongoing deliverables to improve user experience
• Identify actionable insights, suggest recommendations, and influence the direction of the business by effectively communicating metrics and results to stakeholders
• Partner with Data Engineering to craft our data infrastructure investments in support of BI needs and ensure the proper tracking and quality of the data