Cash
Senior Data Scientist, Lifecycle Marketing
Cash, Snowflake, Arizona, United States, 85937
Senior Data Scientist, Lifecycle Marketing
RemoteBay Area, CA, USCompany Description
It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 47 million monthly active customers. We want to redefine the world’s relationship with money to make it more relatable, instantly available, and universally accessible.Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We’ve been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy. Check out our locations, benefits, and more at cash.app/careers.Job Description
The Data Science team at Cash App derives valuable insights from our extremely unique datasets and turns those insights into actions that improve the experience for our customers every day. As a Data Scientist, you will play a critical role in accelerating Cash App’s growth by creating and improving how we measure the impact of all our marketing efforts throughout the user lifecycle.In this role, you’ll be embedded in our Marketing organization and work closely with quantitative finance, marketers, product management as well as other cross-functional partners and explore new opportunities to enable Cash App to become the top provider of primary banking services to our customers.You will :
Own the Cash Lifecycle Marketing holdout reviewBuild models to optimize our marketing efforts to ensure our spend has the best possible ROIDesign and analyze A/B experiments to evaluate the impact of marketing campaigns we runSupport audience sizing and campaign results trackingAnalyze large datasets using SQL and scripting languages to surface actionable insights and opportunities to the Marketing product team and other key stakeholdersPartner directly with the Cash App Marketing org to influence their roadmap and define success metrics to understand the impact to businessApproach problems from first principles, using a variety of statistical and mathematical modeling techniques to research and understand customer behavior & segmentsBuild, forecast, and report on metrics that drive strategy and facilitate decision making for key business initiativesWrite code to effectively process, cleanse, and combine data sources in unique and useful ways, often resulting in curated ETL datasets that are easily used by the broader teamBuild and share data visualizations and self-serve dashboards for your partnersEffectively communicate your work with team leads and cross-functional stakeholders on a regular basisYou have:
A degree in statistics, data science, or similar STEM field with 6+ years of experience in a relevant roleAdvanced proficiency with SQL and data visualization tools (e.g. Tableau, Looker, etc)Experience with scripting and data analysis programming languages, such as Python or RWorked extensively with Causal Inference techniques and off platform dataA knack for turning ambiguous problems into clear deliverables and actionable insightsGone deep with cohort and funnel analyses, a deep understanding statistical concepts such as selection bias, probability distributions, and conditional probabilitiesExperience working with customer acquisition dataManaged relationships with external vendorsTechnologies we use and teach:
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 an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We also consider qualified applicants with criminal histories for employment on our team, and always assess candidates on an individualized basis.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.Block will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and 'fair chance' ordinances.Block takes a market-based approach to pay, and pay may vary depending on your location. U.S locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.To find a location’s zone designation, please refer to this resource.
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RemoteBay Area, CA, USCompany Description
It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 47 million monthly active customers. We want to redefine the world’s relationship with money to make it more relatable, instantly available, and universally accessible.Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We’ve been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy. Check out our locations, benefits, and more at cash.app/careers.Job Description
The Data Science team at Cash App derives valuable insights from our extremely unique datasets and turns those insights into actions that improve the experience for our customers every day. As a Data Scientist, you will play a critical role in accelerating Cash App’s growth by creating and improving how we measure the impact of all our marketing efforts throughout the user lifecycle.In this role, you’ll be embedded in our Marketing organization and work closely with quantitative finance, marketers, product management as well as other cross-functional partners and explore new opportunities to enable Cash App to become the top provider of primary banking services to our customers.You will :
Own the Cash Lifecycle Marketing holdout reviewBuild models to optimize our marketing efforts to ensure our spend has the best possible ROIDesign and analyze A/B experiments to evaluate the impact of marketing campaigns we runSupport audience sizing and campaign results trackingAnalyze large datasets using SQL and scripting languages to surface actionable insights and opportunities to the Marketing product team and other key stakeholdersPartner directly with the Cash App Marketing org to influence their roadmap and define success metrics to understand the impact to businessApproach problems from first principles, using a variety of statistical and mathematical modeling techniques to research and understand customer behavior & segmentsBuild, forecast, and report on metrics that drive strategy and facilitate decision making for key business initiativesWrite code to effectively process, cleanse, and combine data sources in unique and useful ways, often resulting in curated ETL datasets that are easily used by the broader teamBuild and share data visualizations and self-serve dashboards for your partnersEffectively communicate your work with team leads and cross-functional stakeholders on a regular basisYou have:
A degree in statistics, data science, or similar STEM field with 6+ years of experience in a relevant roleAdvanced proficiency with SQL and data visualization tools (e.g. Tableau, Looker, etc)Experience with scripting and data analysis programming languages, such as Python or RWorked extensively with Causal Inference techniques and off platform dataA knack for turning ambiguous problems into clear deliverables and actionable insightsGone deep with cohort and funnel analyses, a deep understanding statistical concepts such as selection bias, probability distributions, and conditional probabilitiesExperience working with customer acquisition dataManaged relationships with external vendorsTechnologies we use and teach:
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 an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We also consider qualified applicants with criminal histories for employment on our team, and always assess candidates on an individualized basis.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.Block will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and 'fair chance' ordinances.Block takes a market-based approach to pay, and pay may vary depending on your location. U.S locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.To find a location’s zone designation, please refer to this resource.
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