The Uniswap Protocol is an open-source protocol for providing liquidity and trading ERC20 tokens on Ethereum. It eliminates trusted intermediaries and unnecessary forms of rent extraction, allowing for safe, accessible, and efficient exchange activity. The protocol is non-upgradable and designed to be censorship resistant.
The Uniswap Protocol and the Uniswap Interface were developed by Uniswap Labs.
Job Short Description
We are seeking a Data Analyst who will work in a highly collaborative and cross-functional setting to empower data-driven decision-making at the company level. This Data Analyst will use analytical skills and machine learning to make better customer experiences. Specifically, they will use knowledge of causal inference and statistics to setup and evaluate experiments, advise the Uniswap Labs team on understanding the drivers of user engagement, and suggest product and business (growth/marketing) directions that could increase future engagement. While keeping a pulse on the product and company, they will predict future changes in business KPIs.
Responsibilities
Develop core metrics and create dashboards to track and measure business performance
Design, conduct and analyze experiments such as A/B tests to guide product decisions
Perform exploratory data analyses and build models to distill insights from data and identify new strategic opportunities
Partner with Product, Growth, Research, Engineering and Leadership to inform, influence, support and execute strategy and product and growth decisions
Design and analyze product experiments to guide product launches
Collaborate with multiple subject matter experts to drive new data initiatives, automate business intelligence reporting, and establish best practices
Create growth/marketing attribution logic and measurement system that enables UL to quantify channel performance / ROI and make spend and resource allocation decisions accordingly
Both for product launches as well as ongoing marketing campaigns
Ongoing user analyses that support revenue and monetization efforts
Attrition analyses (how much attrition can be attributed to fees vs. not)
Customer segmentation (what is the right segmentation based on behaviors we see after fee launch —> will help feed further recommendation on fees)
What are the predictive drivers of revenue (key data science analysis, will lead to honing in on key areas for marketing/product focus)
Requirements
Bachelors/Masters/Ph.D. in quantitative fields (CS, Stats, economics, etc) with 2+ years work experience
Experience with SQL and Python/R
Ability to analyze large data sets in order to quantify performance via metrics or KPIs
Strong communication skills and the ability to present insights to team members in other domains
Ability to prioritize in a highly dynamic start-up environment
An inquisitive mindset and ability to tackle challenges with limited guidance
Nice to Have
Experience in finance
Experience with blockchain data and analytics tools
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