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Develops machine learning models for fraud detection and risk management in global payments, collaborating with engineering and operations to deploy solutions and inform fraud strategy.
Builds and refines fraud detection models (account takeover, card fraud, merchant loss) for Stripe’s global payments platform, collaborating with engineering and risk teams to deploy solutions and drive financial integrity.
About Aaru Aaru builds simulations of human behavior. Each simulation contains a population of AI agents, each representing a person who could plausibly exist in the real world and capable of making decisions within a…
Senior Applied AI/ML Scientist on the Retailer Growth team, building ML systems for paid marketing optimization, bidding, targeting, AEO content creation, and LTV predictions on a wholesale marketplace platform.
Lead a Toronto-based data science and analytics team focused on rider experience, using experimentation, causal inference, and ML models to shape product strategy at a ride-hailing company.
Lead the scientific strategy for Reddit's ads measurement, signal quality, and privacy-safe measurement systems, applying deep experimentation and causal inference expertise at scale.
Senior Data Scientist partnering with AI engineers to analyze real and simulated driving data, design experiments, and build performance metrics that improve the Wayve AI Driver for autonomous vehicles. Core technologies include SQL, Python/R, and statistical analysis.
Senior Product Analyst at an edtech company uses SQL, Python, and Mixpanel to analyze user behavior, run A/B tests, and guide product decisions for online learning platforms serving students worldwide.
The Director of Data Science will lead a team to develop predictive models and customer intelligence strategies for media brands, focusing on personalization, engagement, and product growth. The role involves leveraging Python, SQL, and machine learning to drive actionable insights across web and mobile platforms.
The Data Scientist will develop analytic models and automation tools using R and Python to help advertisers optimize their marketing spend. The role involves interpreting data to provide actionable insights and requires proficiency in statistical modeling techniques.
Customer Insights Analyst using SQL, Python/R, and BI tools to analyze customer behavior, build predictive models (churn, LTV, propensity), and deliver data-driven insights to marketing and brand teams at an international travel company.
A Data Scientist analyzes product usage and public data to produce policy-relevant metrics and dashboards that inform regulators and the public about Anthropic’s AI systems and impact.
Leads data-driven strategy for developer productivity in an AI-first org, defining metrics, experiments, and tooling to measure and improve how engineers work with AI tools like Claude, while partnering closely with engineering leadership.
Data scientist driving commercial decisions for an AI platform, analyzing GTM metrics, running experiments, and building statistical models to optimize customer acquisition and retention.
Build and run marketing measurement systems—marketing mix modeling, geo experiments, and incrementality tests—to determine which marketing spend drives growth and guide budget decisions.
Lead a data-science team to measure and optimize Anthropic’s developer platform, using causal inference and A/B testing to guide API, agent orchestration, and MCP integrations roadmap.
Research Data Scientist on Google's Ads Insights and Measurement team, developing and improving ad products (Search, Display, YouTube) using statistical methods, causal inference, and ML at scale with Python, R, and SQL.
The Senior Data Scientist will build and maintain predictive vulnerability models using ground-truth telemetry to help organizations prioritize security remediation. The role involves end-to-end model development, from feature engineering and training to production deployment and communicating results to stakeholders.
The Machine Learning Scientist will build AI models and agentic workflows to analyze complex biological data, including genomics and single-cell datasets, to drive therapeutic discovery. The role involves developing deep learning systems and foundation models to map relationships between genotype, cell state, and disease mechanisms.
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