Company Description
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 wouldn't work together.
So we expanded into software and started building integrated, omnichannel solutions - to help sellers sell online, manage inventory, offer buy now, pay later functionality through Afterpay, book appointments, engage loyal buyers, and hire and pay staff. Across it all, we've 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 - 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. We're building a significant, meaningful, and lasting business, and we are helping sellers worldwide do the same.
Job Description
The Measurement Machine Learning teams within GTM (go-to-market) organization are instrumental in the development of cutting-edge ML models and algorithms, providing invaluable insights for guiding strategic investment decisions. Our scope includes delivering comprehensive company-wide metrics and GTM channel attribution. We empower a diverse array of stakeholders, spanning marketing, finance, product management, account management, and risk assessment. Additionally, we are dedicated to crafting exceptional data infrastructure and innovative solutions in the realms of data science and machine learning.
We are looking for a senior Machine Learning Engineer with deep expertise in attribution space (just like you!) to join our teams in further expanding Square's measurement system.
You will:

• Be our in-house expert in data driven attribution to fuel Square's growth.
• Build from scratch a suite of data science and machine learning solutions that will make up the core of Square's next generation attribution system.
• Partner with stakeholders from Finance, Marketing, Sales and other GTM channels to refine our growth strategy and inform investment decisions with data.
• Partner with third-party data providers to close the data loop for full funnel attribution.
• Stay up-to-date with the latest advancements and trends in machine learning and data science and apply them to evolve the measurement system.

Qualifications

• 4+ years of data science and ML experience.
• Experience in statistical learning methods for GTM attribution and building from the ground up end-to-end data driven attribution systems which may include marketing mix models (MMM) and algorithmic multi-touch attribution (MTA).
• Experience in building, deploying, maintaining and sunsetting large-scale machine learning models and systems in production environments using TensorFlow, Keras, PyTorch, Scikit-Learn, AWS, Azure, Google Cloud.
• Experience working with senior stakeholders in areas such as Finance, Marketing, Risk and strong communication skills and ability to collaborate with cross-functional teams.

Qualifications

• 4+ years of data science and ML experience.
• Experience in statistical learning methods for GTM attribution and building from the ground up end-to-end data driven attribution systems which may include marketing mix models (MMM) and algorithmic multi-touch attribution (MTA).
• Experience in building, deploying, maintaining and sunsetting large-scale machine learning models and systems in production environments using TensorFlow, Keras, PyTorch, Scikit-Learn, AWS, Azure, Google Cloud.
• Experience working with senior stakeholders in areas such as Finance, Marketing, Risk and strong communication skills and ability to collaborate with cross-functional teams.