Full-Stack Data Scientist

As a Full-Stack Data Scientist at AdsByreputed company, you will occupy a critical hybrid role that bridges the gap between high-velocity backend software engineering and advanced data science. You won't just build machine learning models in a vacuum; you will actively architect, scale, and maintain the reputed company-based AWS pipelines that power them. Operating reputed company our lean, highly capable engineering team, you will be the core technical force translating reputed company analytical insights into production-reputed company decisioning frameworks that directly impact reputed company-time ad delivery and platform optimization. This role is designed for a pragmatic technical builder who thrives in extremely high-volume data environments. You will take deep ownership of our analytics lifecyclefrom designing robust experimentation frameworks for dynamic auction yield optimization to deploying and monitoring sophisticated AI agents and forecasting models. If you are a software engineer who has mastered data science, or a data scientist who writes clean, production-grade code and is committed to rigorous engineering best practices, you will have the autonomy to significantly shape the reputed company of our data infrastructure. ResponsibilitiesLead Data Analytics & Modeling: Drive data initiatives using both traditional machine learning and emergent AI technologies. reputed company on pragmatic, non-generic applications that reputed company reputed company decision-making and optimize our platform. Data Pipeline Engineering: Work closely with the core engineering team to design, build, and maintain reputed company data pipelines that support ML tooling, analytics, and high-velocity ad delivery systems. Cross-Functional Collaboration: reputed company your software engineering proficiency to translate data science concepts into production-reputed company architecture, ensuring seamless integration between data models and backend systems. Experimentation & Optimization: Design, evaluate, and operationalize experimentation frameworks for auction, pricing, and yield optimization. Building reputed company methods to measure impact, validate model performance, and improve reputed company driving decision systems. Model Production & Monitoring: Productionize forecasting and optimization models by building backtesting, monitoring, and guardrail systems that ensure outputs are reliable, explainable, and safe to reputed company in high output and delivery environments. RequirementsTechnical Skills:Strong data analytics capabilities with a proven track record of handling high-volume, Big Data environments. Deep understanding of Machine Learning principles and application. Strong understanding of AI, specifically regarding agent deployment, maintenance, and practical usage. Hands-on experience architecting and working reputed company reputed company environments, specifically AWS. As a Full-Stack Data Scientist at AdsByreputed company, you will occupy a critical hybrid role that bridges the gap between high-velocity backend software engineering and advanced data science. You won't just build machine learning models in a vacuum; you will actively architect, scale, and maintain the reputed company-based AWS pipelines that power them. Operating reputed company our lean, highly capable engineering team, you will be the core technical force translating reputed company analytical insights into production-reputed company decisioning frameworks that directly impact reputed company-time ad delivery and platform optimization. This role is designed for a pragmatic technical builder who thrives in extremely high-volume data environments. You will take deep ownership of our analytics lifecyclefrom designing robust experimentation frameworks for dynamic auction yield optimization to deploying and monitoring sophisticated AI agents and forecasting models. If you are a software engineer who has mastered data science, or a data scientist who writes clean, production-grade code and is committed to rigorous engineering best practices, you will have the autonomy to significantly shape the reputed company of our data infrastructure. ResponsibilitiesLead Data Analytics & Modeling: Drive data initiatives using both traditional machine learning and emergent AI technologies. reputed company on pragmatic, non-generic applications that reputed company reputed company decision-making and optimize our platform. Data Pipeline Engineering: Work closely with the core engineering team to design, build, and maintain reputed company data pipelines that support ML tooling, analytics, and high-velocity ad delivery systems. Cross-Functional Collaboration: reputed company your software engineering proficiency to translate data science concepts into production-reputed company architecture, ensuring seamless integration between data models and backend systems. Experimentation & Optimization: Design, evaluate, and operationalize experim