Senior Data Scientist

GoFasti

. Develop, deploy and maintain predictive models for lifetime value (LTV), churn and retention across mobile apps and web/browser products .

Posted 10/16/2026full-timeRemoteSenior💰 $4,000 - $5,500 per monthWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying predictive models for lifetime value, churn, and retention, utilizing advanced statistical methods and machine learning techniques. Proficient in Python, SQL, and AI tools, with strong communication skills to convey complex analyses to stakeholders.

Highest-signal resume keywords

Predictive ModelingMachine LearningPython ProgrammingStatistical AnalysisData Science

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Predictive ModelingStatistical ModelingMachine LearningPythonSQLData AnalysisModel DeploymentExperiment DesignUser SegmentationCausal Analysis

Soft Skills

Strong CommunicationMentoringProblem StructuringJudgment with Noisy Data

Tools & Technologies

LLM APIsAWSGoogle CloudSageMakerVertex AIMLflowAirflowDbt

Industry Keywords

Consumer AppsAd MonetizationSubscription ModelsAudience SegmentationPersonalization

Tech Stack

Tools & technologies

AirflowAWSCloudPandasPythonScikit-LearnSQL

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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; 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
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

Benefits

Comp & perks

Full-time contract through a payroll platform
Remote work allocated at the client
Opportunity to work with first-class companies around the globe