{"schemaVersion":"jobsearcher.job.v1","id":"66615184ec4635a338b680ef","url":"https://jobsearcher.com/jobs/66615184ec4635a338b680ef","canonicalUrl":"https://jobsearcher.com/jobs/66615184ec4635a338b680ef","title":"Sr Data Scientist (LATAM Remote)","description":"Overview: UPLabs is a dynamic venture studio dedicated to building innovative startup companies from the ground up. Our team thrives on solving complex problems, driving technological advancements, and creating impactful digital products. We're seeking an applied data scientist who ships data products as an engineer, to help us launch the next wave of AI-enabled ventures. This is a hands-on role for someone who can take a problem from data to deployed, monitored data product, with strong statistical judgment along the way. Technical Challenge: In this role, you'll work with large-scale datasets to build scalable machine learning systems and intelligent data platforms. You'll help define how data is stored, processed, referenced, and utilized across AI workflows and operational systems. You'll collaborate closely with engineering, operations, and product teams to build production-grade ML solutions while contributing to architectural decisions around modern data infrastructure. This is a highly hands-on role with strong ownership and technical influence. In This Role, You WillApply statistical and machine learning methods to operationally meaningful problems.Build and refine digital twins and predictive models of physical assets, processes, and operational workflows.Work across hybrid data estates that span on-prem operational systems and modern cloud platforms.Use modern ML frameworks (PyTorch, TensorFlow) where they earn their place, and simpler tools where they don't.Run rigorous, reproducible experimentation using tools like MLflow.Work with large-scale structured and unstructured datasets in Snowflake environmentsDevelop and maintain scalable data pipelines, ETL/ELT workflows, and ML infrastructureDesign systems for storing, processing, and managing ML outputs, embeddings, and AI-generated dataCollaborate with cross-functional teams to translate business problems into scalable data solutions Required Skills & ExpertiseHands-on experience in Data Science, Machine Learning, or ML Engineering roles in Big Data environmentsStrong applied statistics: experimental design, inference, uncertainty quantification, and a working sense of when a result is real versus an artifact of the data.Strong Python and SQL fluency, including comfort with modern distributed SQL engines (e.g., Trino, Spark SQL, or similar).Comfort working across hybrid data environments spanning on-prem operational sources and modern cloud platforms (AWS, Azure, or GCP).Experience with the full ML lifecycle: ingestion, transformation, feature engineering, training, evaluation, deployment, and monitoring.Practical experience with modern ML frameworks (PyTorch or TensorFlow) and experiment tracking tooling (MLflow or comparable).Strong problem-solving skills and ability to work in fast-paced startup environmentsExperience working with Snowflake in production data environments.Nice to HaveExperience delivering models as containerized services like Docker and KubernetesDirect experience with digital twins or applied modeling of physical / operational systems.Time-series, sensor, or streaming data at production scale.Open lakehouse formats (Iceberg, Delta, Hudi) and table-format-aware workflows.Causal inference, A/B testing, or sequential evaluationEdge or hybrid model deployment patterns.Experience with Databricks or comparable platforms. UP.Labs Summary We build high-growth technology startups that enable faster, cleaner, and safer movement of people and goods. Our vision is to transform the moving world by pairing leading corporations and entrepreneurs with a proven methodology for launching and scaling software and hardware companies. We work with corporate investors over a multi-year period to launch a portfolio of mobility-focused ventures. Our team is dedicated to the first year of a new venture's life cycle, from ideation to minimum viable product build (and beyond) to recruiting and hiring the full-time team who will scale the business. Location: Remote","company":"UP","rawCompany":"up","isRemote":true,"isActive":false,"createdAt":"2026-07-19T00:29:07.209Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Sr Data Scientist (LATAM Remote)","description":"Overview: UPLabs is a dynamic venture studio dedicated to building innovative startup companies from the ground up. Our team thrives on solving complex problems, driving technological advancements, and creating impactful digital products. We're seeking an applied data scientist who ships data products as an engineer, to help us launch the next wave of AI-enabled ventures. This is a hands-on role for someone who can take a problem from data to deployed, monitored data product, with strong statistical judgment along the way. Technical Challenge: In this role, you'll work with large-scale datasets to build scalable machine learning systems and intelligent data platforms. You'll help define how data is stored, processed, referenced, and utilized across AI workflows and operational systems. You'll collaborate closely with engineering, operations, and product teams to build production-grade ML solutions while contributing to architectural decisions around modern data infrastructure. This is a highly hands-on role with strong ownership and technical influence. In This Role, You WillApply statistical and machine learning methods to operationally meaningful problems.Build and refine digital twins and predictive models of physical assets, processes, and operational workflows.Work across hybrid data estates that span on-prem operational systems and modern cloud platforms.Use modern ML frameworks (PyTorch, TensorFlow) where they earn their place, and simpler tools where they don't.Run rigorous, reproducible experimentation using tools like MLflow.Work with large-scale structured and unstructured datasets in Snowflake environmentsDevelop and maintain scalable data pipelines, ETL/ELT workflows, and ML infrastructureDesign systems for storing, processing, and managing ML outputs, embeddings, and AI-generated dataCollaborate with cross-functional teams to translate business problems into scalable data solutions Required Skills & ExpertiseHands-on experience in Data Science, Machine Learning, or ML Engineering roles in Big Data environmentsStrong applied statistics: experimental design, inference, uncertainty quantification, and a working sense of when a result is real versus an artifact of the data.Strong Python and SQL fluency, including comfort with modern distributed SQL engines (e.g., Trino, Spark SQL, or similar).Comfort working across hybrid data environments spanning on-prem operational sources and modern cloud platforms (AWS, Azure, or GCP).Experience with the full ML lifecycle: ingestion, transformation, feature engineering, training, evaluation, deployment, and monitoring.Practical experience with modern ML frameworks (PyTorch or TensorFlow) and experiment tracking tooling (MLflow or comparable).Strong problem-solving skills and ability to work in fast-paced startup environmentsExperience working with Snowflake in production data environments.Nice to HaveExperience delivering models as containerized services like Docker and KubernetesDirect experience with digital twins or applied modeling of physical / operational systems.Time-series, sensor, or streaming data at production scale.Open lakehouse formats (Iceberg, Delta, Hudi) and table-format-aware workflows.Causal inference, A/B testing, or sequential evaluationEdge or hybrid model deployment patterns.Experience with Databricks or comparable platforms. UP.Labs Summary We build high-growth technology startups that enable faster, cleaner, and safer movement of people and goods. Our vision is to transform the moving world by pairing leading corporations and entrepreneurs with a proven methodology for launching and scaling software and hardware companies. We work with corporate investors over a multi-year period to launch a portfolio of mobility-focused ventures. Our team is dedicated to the first year of a new venture's life cycle, from ideation to minimum viable product build (and beyond) to recruiting and hiring the full-time team who will scale the business. Location: Remote","datePosted":"2026-07-19T00:29:07.209Z","dateModified":"2026-07-19T00:29:07.209Z","hiringOrganization":{"@type":"Organization","name":"UP","sameAs":"https://jobsearcher.com"},"jobLocationType":"TELECOMMUTE","applicantLocationRequirements":{"@type":"Country","name":"US"},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"66615184ec4635a338b680ef"},"url":"https://jobsearcher.com/jobs/66615184ec4635a338b680ef"}}