As an MLE within the Measurement ML team, you will work collaboratively to apply novel machine learning algorithms and data science methods toward new products that empower our internal business stakeholders. The Measurement team quantifies the impact of Square’s business initiatives through machine learning models in areas such as marketing attribution modeling and forecasting value estimation. We empower stakeholders in marketing, finance, and strategy to make data-driven decisions that will help Square grow.

Measurement ML is part of the Decision Sciences team. We partner with business, product, operations, and engineering teams to guide better decisions using machine learning. We’re a passionate team of specialists, statisticians, and optimizers who are resourceful in distilling questions, wrangling data and driving impactful business decisions.

You Will:

• Collaborate with machine learning engineers and data scientists to train, deploy, and test machine learning models using state-of-the-art techniques.

• Help build the next generation of data products at Square by leveraging ML techniques such as: time series forecasting techniques, causal inference, propensity modeling

You Have: 

• 4 - 7 years of relevant education or industry experience in data science, machine learning, computer science, statistics, or a similar field.

• Ability to produce scalable and robust production-quality code incorporating testing, evaluation, and monitoring.

• Experience in designing and productionizing large-scale distributed systems built around machine learning models and big data.

• Experience with cloud computing platforms is preferred (i.e. Google Cloud Platform)

• Experience with growth (acquisition, engagement, retention) and modeling on marketing data (i.e. attribution, propensity to convert, customer journey mapping, lifetime value, incrementality) is a plus.

Technologies we use:

• Python, Google Cloud Platform, Snowflake, Airflow

We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. 

We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we’re doing to build a workplace that is fair and square? Check out our I+D page. 

Additionally, we consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.

Perks

We want you to be well and thrive. Our global benefits package includes:

• Healthcare coverage
• Retirement Plans
• Employee Stock Purchase Program
• Wellness perks
• Paid parental leave
• Paid time off
• Learning and Development resources

Block, Inc. (NYSE: SQ) is a global technology company with a focus on financial services. Made up of Square, Cash App, Spiral, TIDAL, and TBD, we build tools to help more people access the economy. Square helps sellers run and grow their businesses with its integrated ecosystem of commerce solutions, business software, and banking services. With Cash App, anyone can easily send, spend, or invest their money in stocks or Bitcoin. Spiral (formerly Square Crypto) builds and funds free, open-source Bitcoin projects. Artists use TIDAL to help them succeed as entrepreneurs and connect more deeply with fans. TBD is building an open developer platform to make it easier to access Bitcoin and other blockchain technologies without having to go through an institution.