Data Analyst

Mulberry is disrupting a $40B insurance industry by providing omnichannel merchants a seamless plug-and-play platform from which to offer product insurance. Our backers have invested in companies such as Uber (IPO'd in 2019), Venmo (acquired by PayPal), Pill Pack (acquired by Amazon), Optimizely, and Kaggle (acquired by Alphabet/Google).We call NYC home and are founded by a team of executives who are passionate about e-commerce and building efficiencies through a customer-first outlook. Our platform not only drives revenue for brands, but also improves customer experience and trust in warranty programs.

Mulberry has an open position for a Data Analyst on the Data Science and Analytics team. 

What You’ll Do:

  • Design, implement and maintain reporting dashboards that track key business metrics and provide actionable insights.
  • Conduct research to aid competitive price analyses.
  • Improve internal data dissemination processes and strategies.
  • Develop processes and systems to democratize data within the company.
  • Conduct data analysis to make business recommendations (e.g. cost-benefit, forecasting, impact analysis).
  • Develop and automate reports, iteratively build and prototype dashboards to provide insights at scale, solving for business priorities.
  • Improve analytics practices and documentation.
  • Suggest improvements in the tools and techniques to help scale the team and make it more efficient.

What We’re Seeking:

  • Minimum of 2-3 years of experience
  • Experience extracting data from a diverse set of data sources, including but not limited to PostgresQL, Mongo, Redis, etc.
  • Experience with analytics and dashboarding solutions such as Tableau, Looker, Domo, etc.
  • Familiarity with solving analytical problems using quantitative approaches.
  • Standard Python analytics frameworks and libraries: pandas, numpy, scipy, matplotlib/seaborn/altair, jupyter.
  • Bachelors in computer science, physics, economics, mathematics, operations research, or related quantitative field.

Nice-to-haves:

  • A Masters or PhD in computer science, physics, economics, mathematics, operations research, or related quantitative field.
  • Experience with the data storage, analytics, ETL and data science stack on AWS.
  • Web crawling + scraping experience.
  • Experience with scripting, extracting large sets of data, and design of ETL flows.
  • Excellent written and verbal communication skills.
  • Passion for adding useful features and building new products.
  • Ability to function independently with minimal oversight but also effectively on a team.

Benefits and Perks:

  • Competitive Salary 
  • 1:1 ongoing training and career development with the Co-Founder, and all team members 
  • Equity
  • Full Benefits 
  • Unlimited Paid Time off
  • Gym on-site
  • Strong, vibrant, and fun culture, with lots of outings!
  • Unlimited snacks, pool table, and an awesome rooftop deck!

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