Senior Data Scientist (LATAM Remote)

UP.Labs

6h • Remote

About The Position

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 a highly skilled professional to join our growing team and contribute to our mission of launching the next wave of successful startups.

Technical Challenge:
As a Data Scientist, you will develop and deploy machine learning models that drive product innovation and business insights across our portfolio of startups. Your work will span the full data science lifecycle, from exploratory analysis and feature engineering to model deployment and monitoring in production environments.

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.

Requirements

• Advanced proficiency in Python for data science and machine learning applications
• Strong SQL skills for data extraction, transformation, and analysis
• Solid foundation in statistics and machine learning
• Proven experience with machine learning algorithms including supervised and unsupervised learning techniques
• Working knowledge of AWS cloud services for data science and ML workloads
• Experience with Databricks for collaborative data science and big data processing
• Familiarity with Azure cloud platform and its ML services
• Proficiency in PySpark for distributed data processing and analysis
• Understanding of MLOps practices for model deployment, monitoring, and lifecycle management

Nice To Haves

• Experience with Generative AI technologies and applications
• Knowledge of data engineering principles and pipeline development

Responsibilities

• Design, build, and optimize machine learning models to solve complex business problems, achieving advanced proficiency in ML algorithms and statistical methods
• Analyze and interpret complex datasets to identify trends and opportunities
• Architect and implement end-to-end data science solutions using modern cloud platforms and big data technologies
• Collaborate with engineering teams to integrate data engineering pipelines that support scalable ML workflows
• Communicate findings clearly to technical and non-technical stakeholders
• Deploy and maintain ML models in production, implementing MLOps best practices for monitoring and continuous improvement

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed