Senior Data Scientist (Brazil)

About the Role

CharterUP is seeking a Senior Data Scientist to help build the analytical and modeling capabilities behind our marketplace and pricing systems. You’ll work closely with Product, Engineering, Pricing, and Availability teams to understand marketplace dynamics, develop rigorous analyses, and turn data into recommendations that improve pricing and business performance.

This is a hands-on role where you’ll have the opportunity to work across exploratory analysis, statistical modeling, experimentation, forecasting, and machine learning. You’ll help establish reliable data foundations and shared metrics while solving complex problems in a dynamic marketplace environment.

Title: Senior Data Scientist
Reports to: Staff Data Scientist
Location: Remote, Brazil

What You’ll Do

• Hands-On Data Science: Conduct exploratory analysis, driver analysis, statistical modeling, and machine learning to solve complex marketplace and pricing problems.
• Pricing & Marketplace Analytics: Analyze pricing behavior, supply and demand dynamics, elasticity, conversion, and other marketplace signals to identify opportunities for improvement.
• Experimentation & Modeling: Support the design and analysis of experiments and develop predictive models, forecasts, and other analytical solutions that inform product and business decisions.
• Data Quality & Foundations: Partner with Data Engineering and other technical teams to improve data pipelines, datasets, definitions, and data quality for analytics and machine learning.
• Cross-Functional Partnership: Work closely with Product, Engineering, Pricing, Availability, and business stakeholders to translate ambiguous problems into clear analytical approaches and actionable recommendations.
• Data Storytelling: Communicate complex findings clearly to both technical and non-technical audiences, helping stakeholders understand the implications and tradeoffs behind your recommendations.
• Production ML: Contribute to the development, deployment, monitoring, and improvement of machine learning models as the team's data science capabilities mature.
• Best Practices: Help establish strong practices around statistical rigor, experimentation, reproducible analysis, and data science workflows.

Key Initial Objectives

• Partner with the Staff Data Scientist on a rigorous first deep dive into pricing and marketplace economics.
• Deliver structured, decision-ready analysis that directly informs the pricing roadmap.
• Help identify and document data quality gaps encountered during analysis, in partnership with Engineering.
• Contribute to shared metric definitions used consistently across Product, Finance, and Revenue.
• Begin laying the groundwork for scalable forecasting and machine learning capabilities.

What You’ll Bring

• Data Science Experience: 4–7+ years of experience in data science, analytics, or a related quantitative field, with experience independently owning complex analytical projects.
• Machine Learning & Statistical Expertise: Strong experience applying statistical modeling, machine learning, experimentation, forecasting, or optimization to solve business problems. Experience with pricing, marketplaces, supply and demand, or other dynamic systems is highly valued.
• Technical Expertise: Advanced proficiency in SQL and Python or R, with experience working with large datasets and building reliable analytical datasets.
• Analytical Problem Solving: Ability to break down ambiguous business problems, identify the right analytical approach, and turn complex data into practical recommendations.
• Business Acumen: Ability to connect analytical findings to business outcomes and communicate the implications of your work to Product, Engineering, and business stakeholders.
• Cross-Functional Collaboration: Strong communication and partnership skills, with the ability to work effectively with both technical and non-technical teams.
• Production ML: Experience deploying and maintaining machine learning models in production is a plus.
• AI/ML: Familiarity with modern AI/ML techniques, LLMs, or NLP is a plus.
• Marketplace Experience: Experience in pricing, marketplaces, transportation, travel, e-commerce, logistics, or another environment with complex supply and demand dynamics is a plus.

Recruiting Process

• Step 1 - Video call: Talent Acquisition interview
• Step 2 - Video call: Hiring Manager interview
• Step 3 - Video call: Team interviews (x3)
• Step 4 - Video call: Case Study & Panel Presentation
• Step 5 - Offer & reference check
• Welcome aboard!

Compensation

$6,000–$7,000 USD per month

About the Role

CharterUP is seeking a Senior Data Scientist to help build the analytical and modeling capabilities behind our marketplace and pricing systems. You’ll work closely with Product, Engineering, Pricing, and Availability teams to understand marketplace dynamics, develop rigorous analyses, and turn data into recommendations that improve pricing and business performance.

This is a hands-on role where you’ll have the opportunity to work across exploratory analysis, statistical modeling, experimentation, forecasting, and machine learning. You’ll help establish reliable data foundations and shared metrics while solving complex problems in a dynamic marketplace environment.

Title: Senior Data Scientist
Reports to: Staff Data Scientist
Location: Remote, Brazil

What You’ll Do

• Hands-On Data Science: Conduct exploratory analysis, driver analysis, statistical modeling, and machine learning to solve complex marketplace and pricing problems.
• Pricing & Marketplace Analytics: Analyze pricing behavior, supply and demand dynamics, elasticity, conversion, and other marketplace signals to identify opportunities for improvement.
• Experimentation & Modeling: Support the design and analysis of experiments and develop predictive models, forecasts, and other analytical solutions that inform product and business decisions.
• Data Quality & Foundations: Partner with Data Engineering and other technical teams to improve data pipelines, datasets, definitions, and data quality for analytics and machine learning.
• Cross-Functional Partnership: Work closely with Product, Engineering, Pricing, Availability, and business stakeholders to translate ambiguous problems into clear analytical approaches and actionable recommendations.
• Data Storytelling: Communicate complex findings clearly to both technical and non-technical audiences, helping stakeholders understand the implications and tradeoffs behind your recommendations.
• Production ML: Contribute to the development, deployment, monitoring, and improvement of machine learning models as the team's data science capabilities mature.
• Best Practices: Help establish strong practices around statistical rigor, experimentation, reproducible analysis, and data science workflows.

Key Initial Objectives

• Partner with the Staff Data Scientist on a rigorous first deep dive into pricing and marketplace economics.
• Deliver structured, decision-ready analysis that directly informs the pricing roadmap.
• Help identify and document data quality gaps encountered during analysis, in partnership with Engineering.
• Contribute to shared metric definitions used consistently across Product, Finance, and Revenue.
• Begin laying the groundwork for scalable forecasting and machine learning capabilities.

What You’ll Bring

• Data Science Experience: 4–7+ years of experience in data science, analytics, or a related quantitative field, with experience independently owning complex analytical projects.
• Machine Learning & Statistical Expertise: Strong experience applying statistical modeling, machine learning, experimentation, forecasting, or optimization to solve business problems. Experience with pricing, marketplaces, supply and demand, or other dynamic systems is highly valued.
• Technical Expertise: Advanced proficiency in SQL and Python or R, with experience working with large datasets and building reliable analytical datasets.
• Analytical Problem Solving: Ability to break down ambiguous business problems, identify the right analytical approach, and turn complex data into practical recommendations.
• Business Acumen: Ability to connect analytical findings to business outcomes and communicate the implications of your work to Product, Engineering, and business stakeholders.
• Cross-Functional Collaboration: Strong communication and partnership skills, with the ability to work effectively with both technical and non-technical teams.
• Production ML: Experience deploying and maintaining machine learning models in production is a plus.
• AI/ML: Familiarity with modern AI/ML techniques, LLMs, or NLP is a plus.
• Marketplace Experience: Experience in pricing, marketplaces, transportation, travel, e-commerce, logistics, or another environment with complex supply and demand dynamics is a plus.

Recruiting Process

• Step 1 - Video call: Talent Acquisition interview
• Step 2 - Video call: Hiring Manager interview
• Step 3 - Video call: Team interviews (x3)
• Step 4 - Video call: Case Study & Panel Presentation
• Step 5 - Offer & reference check
• Welcome aboard!

Compensation

$6,000–$7,000 USD per month