Data Analyst ( US REMOTE)

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Data Analyst ( US REMOTE)

New York, NY /

Data – Insights & Analytics /

Full-Time

/ Remote

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Before we dive into the role, let’s talk about flexibility. At Zip, our office is in New York City but we can hire from anywhere across the United States. Our Zipsters can choose where and when they work by taking full advantage of our hybrid-work environment.

So whether you’re fully remote, mostly in the office or a mix of the two, you’ll be empowered to do whatever brings out your best.

About Us

We are Zip, a global Buy Now, Pay Later company providing fair and seamless solutions that simplify how millions of people pay. Our journey began in Australia, has taken us to multiple different markets and we’re just getting started.

We exist to create a world where people can live fearlessly today, knowing they’re in control of tomorrow. Focused on product innovation that puts people at the centre, we put the financial well-being of our customers and merchant partners at the heart of everything that we do.

About The Role

We’re looking for a data fanatic to join a team of analysts that are responsible for building Zip’s data platforms. We need people who understand data at a granular level – they don’t rely on any one tool but rather understand them all, and each of their pros and cons. This is a unique opportunity to build the data strategy and architecture at a data-driven startup that’s changing the world of finance, shoulder-to-shoulder with a tight team that has your back.

What you’ll do

• Be responsible for Zip’s data analytics platforms across key departments with a dominant focus on marketing.
• Partner closely with business leaders to create and enable analytics around how Zip attracts, engages and retains customers in our App.
• Build and maintain data analytics dashboards and other tools (alation, tableau, amplitude, optimizely).
• Identify opportunities in the business operations for data-based recommendations.
• Bring a strong track record of analytics enablement to companies with a focus on fintech.
• Connect vague business questions to data projects to create new analytics capabilities; this will require strong SQL knowledge, data modeling experience is a plus.
• Work with our complex and large volume of data to understand trends, behaviors and opportunities for revenue growth.
• Communicate insights with senior stakeholders and team members.
• Conduct pre and post implementation reviews and present compelling campaign results and actionable insights.
• Promote a high standard of campaign and customer analytics within Marketing to drive successful program outcomes using data led insights.
• Collaborate with the broader Data & Risk Team to share ideas and discuss analytical approaches in the interests of promoting continual development.

What you’ll bring

• 2-4 years of professional, full-time data experience, this includes experience with a coding language, SQL preferred, data modeling, and a BI tool, tableau preferred.
• An excellent addition to our culture: You believe and want to participate in a blameless culture which focuses on process and technology. You feel accountable for everything you do and that sense of urgency has been driving you your entire life. You like to have a good time while getting things done. When we say a “team player” we mean it - you have a crisp high-five and funny stories to tell. You have your team’s back, and the team has yours.
• A yearning to learn new things: You know that there’s always more to learn, and it bothers you that there isn’t enough time in the day to learn about the next topic. You’re up-to-date on new trends in data – you know who’s using what to solve various problems and are excited for the next release of your favorite tool. If you can handle being thrown in the deep end of the pool, this team’s for you.
• The ability to solve big picture problems: Proactively identify reports, dashboards, and analysis needed by the business. Partner with Product & Engineering teams to strategize and drive user growth.
• Comfort in uncertainty: You’re comfortable in the weeds pulling, cleaning, analyzing, and transforming raw data into insightful, viz-ual findings. You