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A Senior Data Scientist who designs and deploys advanced ML systems (recommender engines, NLP, classification) to personalize user experiences and measure true business impact via causal inference (e.g., uplift modeling).
Build and deploy ML models for media, ad-tech and e-commerce: recommendations, real-time personalization, pricing and bidding engines that directly lift CTR, eCPM and revenue.
Build and deploy ML models for personalization and causal inference, focusing on recommender systems and uplift modeling using Python, PySpark, and cloud platforms.
Lead Data Analyst oversees experimentation, KPIs, and scalable reporting for Żappka’s digital products using SQL, Python, and BI tools to drive growth and business decisions.
Build and deploy ML models to predict user responses and optimize first-price ad auctions with bid shading, pacing, and feedback loops for a large media, adtech, and e-commerce platform.
Lead quantitative UX research for Target’s internal tools, designing surveys and measurement programs to track usability and business impact for enterprise users.
Lead advanced ML and causal-inference modeling to drive strategic decisions, mentor data scientists, and communicate insights to senior stakeholders at Microsoft.
Leads advanced data science and causal inference for Microsoft’s customer support AI systems, designing experiments, mentoring teams, and advising executives on high-stakes technical decisions using Python, SQL, and ML frameworks.
Leads a team building and deploying large neural networks for banking use cases like customer communications, upselling, and uplift modeling, ensuring solutions scale into production.
Leads end-to-end data science for Foodsmart’s member journey, owning analytics, experimentation, and causal inference to drive activation, retention, and funnel optimization across marketing, product, and clinical operations using full-stack tools like dbt, Statsig, and AI agents.
Lead data-science projects that blend causal inference, ML, and robust pipelines to build trustworthy analytics for mission-critical decisions in government and industry.
Leads AI-powered analytics platforms for commercial decision-making in pharma, owning product strategy, agentic AI tools, and cross-functional teams to embed actionable insights into marketing and market access workflows.
Build causal and predictive models to optimize Amazon Music’s marketing, analyze customer data with SQL/Python, and embed AI into self-service analytics tools.
Build and deploy ML models for business decisions and optimize AI agentic systems like conversational tools, using Python, SQL, and libraries such as PyTorch.
Build geospatial ML models to optimize final-mile delivery routes, reduce costs, and improve customer/driver experience using GPS, traffic, and routing data.
Lead end-to-end data science projects at Zillow using advanced analytics, machine learning (Python, R, SQL), and experimentation frameworks to improve real estate products and customer experiences, working remotely across the US.
Leads a data science team to build AI-driven systems for Amazon’s customer service network, blending causal inference, workforce strategy, and real-time observability to optimize routing, capacity planning, and human-AI collaboration across automation and human-assisted channels.
Join Ferrovial: Where Innovation Meets Opportunity Are you ready to elevate your career with a global leader in infrastructure solving complex problems and generating a positive outcome on people’s lives? At Ferrovial…
We’re here for one reason and one reason only – to cure cancer. Every moment is dedicated to developing treatments and every action moves us one step closer to our goal. We’ve made incredible scientific breakthroughs…
Builds and deploys LLM-powered agentic workflows for network troubleshooting using LangGraph, MCP servers, and Kubernetes, focusing on reasoning pipelines, tool integration, and production-scale AI systems.
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