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Product Data Analyst - Remote USA

Bird logo

Location
United States
Bird

Job Description

Company Overview:

Bird’s cleaner, affordable, and on-demand mobility solutions are available in cities globally. We take a collaborative, community-first approach to micromobility. Bird partners closely with the cities in which it operates to provide a reliable and affordable transportation option for people who live and work there.

Role Overview:

The Data Team at Bird is an integral component of every facet of the business from strategic initiatives to tactical effectiveness, and is a key resource in developing Bird's product and procedures. As a Senior Data Analyst you will support the product team in their pursuit to make the cities we operate in more liveable, sustainable, and efficient. You will be embedded with a product team and be assigned a stakeholder who you will proactively work with to develop a roadmap of data priorities and execute against those priorities as we develop data-driven products, features, and strategies to support the growth of the business.

Key Responsibilities:

  • Leverage your experience and skills to understand and share how our users (riders, operators, etc) interact with and use our core business products
  • Partner with Product to help define and analyze metrics that inform the success of products and to monitor product adoption & health across our vehicle and marketplace ecosystems
  • Partner with Engineering and Data Science to develop and implement experiments to test hypothesis for which changes will drive product adoption and growth
  • Partner with Engineering to develop, implement, and test experiments meant to drive product adoption or usage
  • Design the data strategy, select applicable statistical methods and synthesize results from complex A/B multivariate tests
  • Communicate via compelling, easy-to-use dashboards or analysis the state of our business and products, operational performance, experiment results, and potential opportunities for growth
  • Influence and inform product teams through write-ups, meeting and presentations of data-based recommendations
  • Write ETLs to make product data consumable for our internal data and product customers
  • Conduct hands-on modeling/analytics retrieving, compiling, and analyzing large volumes of data from disparate databases into distilled, actionable information and insights
  • Champion the analytics process – from measurement strategies, data preparation, modeling, cleansing and evaluation
  • Lead by example and help educate business stakeholders with varying technical or non-technical backgrounds

Required Qualifications:

  • Bachelor's degree in a quantitative field, economics, or finance from a competitive school
  • Highly Proficient in SQL
  • Fluency in either R or Python strongly desired: candidates should be able to acquire, manipulate, transform, and visualize data using these languages
  • 4+ years of experience using data to facilitate business or product decisions

Preferred Qualifications:

  • Graduate degree in a quantitative field, economics, or finance from a competitive school
  • Experience designing and analyzing randomized control trials
  • Ability to develop and manage an experimentation roadmap in collaboration with Product and Operations team
  • Understanding of data warehouse architecture and data design
  • Responsible and reliable to the people you work with - this is a team effort!
  • Growth mindset: you seek out learning opportunities for yourself and the team
  • Effective communication skills: you can build the story and then tell it just as well
  • Project management savvy: you expect best from your peers to get joint projects done well
  • Seize opportunities and willing to go beyond the task at hand
  • Responsiveness: you deliver timely, digestible answers to complex asks
  • Constantly think of ways to improve our products and the business

Culture at Bird

We're an ambitious, smart and open-minded team that is passionate about our mission. Each day is unlike the last, as we’re constantly moving forward, challenging each other, and working together to create the future of micro-mobility.

Bird is the world

Bird stands for a culture of inclusion. We celebrate different backgrounds, experiences, and perspectives encouraging everyone to bring their authentic selves to work. We have a diverse environment that empowers our team to feel comfortable when they voice their opinions. For these reasons and more Bird is a proud equal employment opportunity employer. We welcome everyone regardless of their race, colour, religion, sex, national origin, age, disability, veteran status, or genetics, and we are dedicated to providing an inclusive, open, and diverse work environment.

Sound like a place you’d like to work? Sweet. Let’s chat.

Advice from our career coach

A successful applicant for the Senior Data Analyst role at Bird should have a strong background in quantitative fields, a proficiency in SQL, and experience using R or Python to manipulate and visualize data. To stand out, candidates should showcase their ability to translate data insights into actionable recommendations, collaborate effectively with product and engineering teams, and demonstrate a growth mindset and proactive problem-solving skills. Additionally, emphasizing project management experience, communication skills, and a commitment to continuous learning and improvement will make an applicant more competitive.

  • Highlight your quantitative background and proficiency in SQL, R, or Python
  • Demonstrate your ability to translate data insights into actionable recommendations for product and business decisions
  • Showcase your experience collaborating effectively with cross-functional teams, including product and engineering
  • Emphasize your growth mindset, proactive problem-solving skills, and commitment to continuous learning
  • Highlight your project management experience, communication skills, and ability to drive improvements in products and processes
  • Show a track record of delivering timely and digestible answers to complex data-related questions

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