About the company
Since we opened our doors in 2009, the world of commerce has evolved immensely, and so has Square. After enabling anyone to take payments and never miss a sale, we saw sellers stymied by disparate, outmoded products and tools that wouldnāt work together. To solve this problem, we expanded into software and built integrated solutions to help sellers sell online, manage inventory, book appointments, engage loyal buyers, and hire and pay staff. Across it all, weāve embedded financial services tools at the point of sale, so merchants can access a business loan and manage their cash flow in one place. Afterpay furthers our goal to provide omnichannel tools that unlock meaningful value and growth, enabling sellers to capture the next generation shopper, increase order sizes, and compete at a larger scale. Today, we are a partner to sellers of all sizes ā large, enterprise-scale businesses with complex operations, sellers just starting, as well as merchants who began selling with Square and have grown larger over time. As our sellers grow, so do our solutions. There is a massive opportunity in front of us. Weāre building a significant, meaningful, and lasting business, and we are helping sellers worldwide do the same.
Job Summary
You will:
šSpearhead the effort to architect and build the next-generation, data-driven attribution system for Square. This attribution system is a top priority of Squareās GTM effort to optimize investment and drive growth, and will be based on solid scientific methodology that is defensible and explainable šBuild various attribution models as the building blocks for the next-generation attribution system by utilizing techniques such as MTA (multi-touch attribution), MMM (Marketing Mix Modeling), Incrementality test as well as other emerging technologies šCollaborate with MLEs to develop and evaluate advanced MTA by utilizing a combination of first party and third party data šWork with data scientists across a wide organization such as marketing, sales, product to design and evaluate attribution models šPartner with data engineers to evaluate, improve and potentially revamp existing data pipelines to achieve higher data quality, lower latency and be ready for the next-generation attribution system šTake an econometric, holistic view to design and evaluate ROI and marginal ROI metrics that will go hand-in-hand with attribution system to guide Squareās investment to generate best return and fuel growth šCollaborate with cross-functional partners. To name a few: finance, marketing, sales, product, seller lifecycle. šResearch and explore cutting edge methodologies, stay up to date with the latest industry trends and best practices
Qualifications
šDeep expertise in statistical and machine learning methods for go-to-market attribution and hands-on experience with building end-to-end attribution systems that may include Marketing Mix Modeling (MMM) algorithmic multi-touch attribution (MTA) š6+ years of data science experience šThorough understanding of economics in go-to-market including but not limited to incrementality, ROI, marginal ROI, elasticity šExpert in variety of go-to-market experimentation techniques šExperience in full-funnel marketing: metrics set up, performance evaluation and optimization šAdvanced proficiency in programming languages such as Python, R, SQL šStrong ability to coordinate needs from product, finance, go-to-market to form data and data science strategy and align across the organization šTrack record of working effectively and efficiently with product partners to plan, deliver and evaluate martech product šDemonstrated ability to clean and preprocess data using tools like Pandas, NumPy šProven ability to mentor and coach more junior data scientists šStrong communication skills and ability to collaborate with cross-functional teams and proven record to influence business strategy
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