Data Scientist
Latam
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About Airtm:Airtm exists because money in Latin America is broken. It constantly loses its value making it difficult for people to preserve their wealth and to participate in the global economy.Our mission is to free Latin America´s money by giving everyone in the region a globally connected dollar account. With Airtm anyone can save, spend, send and receive dollars as if they were in the United States, More than two million have already signed up for financial freedom. With your help building and operating our Controllership and Financial Operations functions we will be able to give financial freedom to another 98 million.
About the Role:The Data Analytics team works to deliver different data products to our internal and external customers so that we can improve our internal efficiency with important insights and improve the way we serve our customers.As a Data Scientist in Airtm, you will work closely with business partners to deliver actionable knowledge to different areas like Marketplace, Commops, Compliance, and Growth. Also, you will need to collaborate with other analysts and engineers to deliver top-quality data products.
What you’ll be responsible for:-Design, build and maintain data pipelines needed to integrate useful data to keep track of anything related with our business.-Plan and implement different AB tests to gain valuable insights.-Prepare ad hoc EDAs, reports, and visualizations.-Collaborate with other peers to design and build data models in our Data Warehouse , as well as metrics that enable clear business understanding.-Contribute to grow our analytical culture.
Must haves:-Engineering, Mathematics, Computer Science, or related background.-Proficiency with SQL (3+ years), DBT (2+ years), Tableau (+2 years) and Python (3+ years).-Statistical competence, experience on parametric and non-parametric hypothetical tests, and time series analysis.-Ability to build machine learning models, deploy and monitor them.-Strong analytical and communication skills.-Fluency in English.
Nice to haves:-Experience using AWS services like Redshift, Lambda, Step Functions, MWAA, and Glue.-Experience in Fintech and/or marketplace industries.
About the Role:The Data Analytics team works to deliver different data products to our internal and external customers so that we can improve our internal efficiency with important insights and improve the way we serve our customers.As a Data Scientist in Airtm, you will work closely with business partners to deliver actionable knowledge to different areas like Marketplace, Commops, Compliance, and Growth. Also, you will need to collaborate with other analysts and engineers to deliver top-quality data products.
What you’ll be responsible for:-Design, build and maintain data pipelines needed to integrate useful data to keep track of anything related with our business.-Plan and implement different AB tests to gain valuable insights.-Prepare ad hoc EDAs, reports, and visualizations.-Collaborate with other peers to design and build data models in our Data Warehouse , as well as metrics that enable clear business understanding.-Contribute to grow our analytical culture.
Must haves:-Engineering, Mathematics, Computer Science, or related background.-Proficiency with SQL (3+ years), DBT (2+ years), Tableau (+2 years) and Python (3+ years).-Statistical competence, experience on parametric and non-parametric hypothetical tests, and time series analysis.-Ability to build machine learning models, deploy and monitor them.-Strong analytical and communication skills.-Fluency in English.
Nice to haves:-Experience using AWS services like Redshift, Lambda, Step Functions, MWAA, and Glue.-Experience in Fintech and/or marketplace industries.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Job stats:
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Category:
Data Science Jobs
Tags: AWS Computer Science Data Analytics Data pipelines Data warehouse dbt Engineering FinTech Lambda Machine Learning Mathematics ML models Pipelines Python Redshift SQL Statistics Step Functions Tableau
Perks/benefits: Career development
Regions:
North America
South America
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