Senior Data Scientist

Eightpoint; Brasil; Remote; BRL 350,000 - 550,000; Full time

Job summary

Eightpoint is seeking a Senior Data Scientist for remote contract work. You will develop, deploy and maintain predictive models for LTV, churn and retention across mobile apps and web products.

Own the modeling roadmap, build segmentation and propensity models, and improve accuracy via validation and data exploration. You will design experiments, apply LLMs to unstructured data, and collaborate with data engineers to productionize models.

Qualifications

• 5+ years of experience in data science, statistical modeling or machine learning, ideally with consumer app or web data.
• Strong Python (pandas, scikit-learn or similar) and advanced SQL.
• Experience deploying models to production and monitoring them over time.
• Solid grounding in statistics, forecasting and experimentation.
• Hands-on experience with LLM APIs, prompt design or building AI-powered data tools.
• Daily use of AI tools as a development partner, such as Claude, Claude Code or Claude Cowork.
• Sound judgment with incomplete or noisy data; you structure the problem before reaching for a tool.
• Strong communication skills, including turning complex analysis into clear business recommendations.
• Fluent English and at least 4 hours of overlap with US Eastern business hours (remote roles).

Responsibilities

• Develop, deploy and maintain predictive models for lifetime value (LTV), churn and retention across our mobile apps and web/browser products.
• Own the modeling roadmap for your area, from problem framing through production and ongoing monitoring.
• Build cohort and LTV models that inform user acquisition budgets and payback decisions.
• Build user segmentation and propensity models that support personalization and targeting.
• Improve model accuracy over time through validation, backtesting and new data sources.
• Design experiments and causal analyses that measure the true impact of product and marketing changes.
• Identify early behavioral signals that predict conversion, churn and long-term value.
• Apply LLMs and machine learning to classify unstructured text and behavioral signals into interest categories, powering personalization and audience targeting.
• Partner with data engineering to productionize models and keep their inputs reliable.
• Build internal AI-powered analytics tools and data products.
• Explain model results, assumptions and confidence levels clearly to stakeholders and leadership.
• Set modeling standards, documentation and best practices for the team.
• Mentor other analysts and data scientists and share best practices across the team.

Skills

Python

SQL

Model deployment

LLMs / APIs

Communication

Tools

SageMaker

Vertex AI

Job description

Senior Data ScientistRemote (Contract)Eightpoint is a global multi-platform application development company. We focus on building highly effective digital offerings that can maximize value for our advertisers, publishers, partners, and users. Eightpoint operates in multiple different product lines on a global landscape. We have products that include mobile applications, browser extensions, desktop apps, digital media, and digital advertising; we also partner with top-tier companies and are currently Yahoo’s #2 partner for driving traffic. These diverse mobile and web solutions allow advertisers to optimize for a highly targeted audience reach. Combining best-in-class industry expertise and consumer interests with proprietary big-data insights, we develop fine-tuned apps that offer optimal user engagement at scale.

What You’ll Do

Predictive Modeling

• Develop, deploy and maintain predictive models for lifetime value (LTV), churn and retention across our mobile apps and web/browser products
• Own the modeling roadmap for your area, from problem framing through production and ongoing monitoring
• Build cohort and LTV models that inform user acquisition budgets and payback decisions
• Build user segmentation and propensity models that support personalization and targeting
• Improve model accuracy over time through validation, backtesting and new data sources

Experimentation & Causal Inference

• Design experiments and causal analyses that measure the true impact of product and marketing changes
• Identify early behavioral signals that predict conversion, churn and long-term value

AI & Data Products

• Apply LLMs and machine learning to classify unstructured text and behavioral signals into interest categories (such as the IAB taxonomy) and product and brand intent, powering personalization and audience targeting
• Partner with data engineering to productionize models and keep their inputs reliable
• Build internal AI-powered analytics tools and data products

Communication

• Explain model results, assumptions and confidence levels clearly to stakeholders and leadership
• Set modeling standards, documentation and best practices for the team
• Mentor other analysts and data scientists and share best practices across the team

Who You Are

• 5+ years of experience in data science, statistical modeling or machine learning, ideally with consumer app or web data
• Strong Python (pandas, scikit-learn or similar) and advanced SQL
• Experience deploying models to production and monitoring them over time
• Solid grounding in statistics, forecasting and experimentation
• Hands-on experience with LLM APIs, prompt design or building AI-powered data tools
• Daily use of AI tools as a development partner, such as Claude, Claude Code or Claude Cowork
• Sound judgment with incomplete or noisy data; you structure the problem before reaching for a tool
• Strong communication skills, including turning complex analysis into clear business recommendations
• Fluent English and at least 4 hours of overlap with US Eastern business hours (remote roles)

Nice to Have

• Experience with ad-monetized or subscription consumer apps
• Experience with recommendation systems, personalization or audience segmentation for ad targeting
• Experience with ML platforms on AWS or Google Cloud, such as SageMaker or Vertex AI
• Familiarity with MLOps and orchestration tools such as MLflow, Airflow or dbt
• Familiarity with Bayesian methods, uplift modeling or multi-armed bandits