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VP – Data Science & Analytics

VP – Data Science & Analytics

CompanyFashion Nova
LocationLos Angeles, CA, USA
Salary$246022 – $360000
TypeFull-Time
DegreesBachelor’s
Experience LevelSenior, Expert or higher

Requirements

  • Bachelor’s degree or foreign equivalent in Computer Science, Electronics Engineering or related field
  • Five (5) years of post-baccalaureate experience as a V.P. or Director of Data Science and Analytics, Director of Finance and Strategy-eCommerce or in a related position
  • Experience must include advanced analytics, statistical analysis, AI & Machine Learning models; XGBoost and Random Forest algorithms; Geo-based statistical A/B tests; statistical methods including machine learning algorithms (regression, clustering) and data visualization tools, Tableau and MicroStrategy; SQL, data mining, Python; and A/B Testing and Experiment Design.

Responsibilities

  • Build a high performing, responsive team of data scientists, and analysts that can gather and synthesize data quickly and accurately
  • Partner with engineering and product teams to design experiments, analyze results, and deliver insights
  • Support data-informed decision-making across the entire company
  • Partner with the product team to design and analyze root cause effective A/B tests
  • Work closely with Marketing to optimize monthly advertising budgets based on customer insights
  • Participate with Fashion Nova’s executive team, help set business strategy, initiate and debate key strategic topics and opportunities from your team’s work, and drive bold high-impact decisions
  • Collaborate with cross-functional partners in product, engineering, operations, finance, and marketing to define and build data-informed business strategy
  • Determine how to leverage data science, machine learning, and other analytical techniques to offer actionable insights and improve user experiences
  • Provide timely turnarounds on data requests for ‘one-off’ activities, such as acquisition, partnership analyses and new product initiatives
  • Utilize strong technical expertise to coach and develop the team, guiding them on career paths and fostering their growth
  • Position supervises one data engineer and two data analysts.

Preferred Qualifications

    No preferred qualifications provided.