Up Labs

Up Labs

Sr Data Scientist (LATAM Remote)

USA · Senior · Full-time

Sponsorship not specifiedDetected 64 days ago
PythonSQLSnowflakeDatabricksAWSGCPAzureCloud PlatformsDockerKubernetesMachine LearningTensorFlowPyTorchSparkData EngineeringData ScienceStatisticsA/B TestingDesign SystemsExperimental DesignProblem Solving

About the role

  • 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.

Responsibilities

  • 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.
  • Build and refine digital twins and predictive models of physical assets, processes, and operational workflows.
  • UP.Labs Summary We build high-growth technology startups that enable faster, cleaner, and safer movement of people and goods.
  • 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.

Requirements

  • 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 environments Experience working with Snowflake in production data environments.

Nice to have

  • Experience delivering models as containerized services like Docker and Kubernetes Direct 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.
  • Experience with Databricks or comparable platforms.
  • We work with corporate investors over a multi-year period to launch a portfolio of mobility-focused ventures.

Skills

  • 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).
  • 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.

Benefits

  • 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.
  • Technical Challenge: In this role, you'll work with large-scale datasets to build scalable machine learning systems and intelligent data platforms.
  • In This Role, You Will Apply statistical and machine learning methods to operationally meaningful problems.

This listing is sourced directly from Up Labs's careers page and normalized into a canonical job model.