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The Data Analyst will join the Revenue Intelligence team to monitor financial performance, build predictive models, and develop anomaly detection systems for an e-commerce platform. The role involves using SQL and Python to perform causal inference and translate complex data into actionable insights for senior leadership.
Lead a global ML and backend engineering org at HelloFresh, building AI-driven pricing, benefit optimization, and customer lifetime-value systems across Berlin, Warsaw, NYC, Boulder, and Toronto.
Minute Media is seeking a Data Scientist to optimize programmatic advertising monetization and user lifetime value through advanced modeling and experimentation. The role involves building production-ready models, managing an experimentation platform, and providing technical leadership within the company's ad-tech ecosystem.
Build production-grade data models in BigQuery and dbt to power product decisions for an AI-driven adtech platform, partnering with engineering and product teams.
The Technical Program Manager will serve as the operational backbone for Doctolib's AI Research Lab, managing processes, cross-functional roadmaps, and academic-industry collaborations. The role requires balancing research needs with product goals while navigating complex administrative and technical dependencies.
Builds and deploys AI-driven predictive models for cardiovascular risk, user engagement, and health recommendations in a healthcare-focused AI platform.
Overview Major League Soccer's Strategy and Business Intelligence group is tasked with supporting strategic decision making and resource allocation across the League - with a focus on driving fan growth, revenue…
Lead data-science strategy and execution for drug development, applying AI/ML and advanced analytics to clinical, omics, and biomarker data to inform clinical decisions and regulatory strategy.
Senior ML Engineer building production ML systems on Databricks, Snowflake, and AWS for identity resolution, audience targeting, and content personalization at Warner Bros. Discovery's Data & Audience Platform team in Hyderabad.
Intuit is seeking an experienced Data Science leader to manage our People Analytics Data Science & Research team at Intuit. Our team partners closely with Intuit's HR leaders, COEs, Finance, and business…
Work Location: Toronto, Ontario, Canada Hours: 37.5 Line of Business: Analytics, Insights, & Artificial Intelligence Pay Details: $105,500 - $125,000 CAD The pay details posted reflect a temporary market premium…
Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves,…
Description: The Applied AI Scientist - Commercial builds and deploys machine learning and agentic AI systems that improve pricing, contracting, customer, and portfolio decisions across Amneal's generics and…
Senior Data Scientist generating medical insights and forecasts from longitudinal clinical datasets (genomics, imaging, labs) at a membership-based healthcare practice, using Python, SQL, Snowflake, dbt, and Omni Analytics.
Product Data Scientist embedded in Product Management for a Home Improvement lending product, driving analytics, A/B testing, ML models, and data pipelines using SQL, dbt, and Python/R.
Senior Data Scientist partnering with the SEO Marketing team to drive company-level SEO growth through metric development, causal inference experiments, A/B/MVT testing, and machine learning on web architecture, using SQL and Python/R.
Backend engineer on Grab's experimentation platform (GrabX), building and optimizing high-scale A/B testing infrastructure using microservices, relational/NoSQL databases, and containerized cloud deployments.
An Applied Scientist building AI/ML models and systems for high-stakes decisions in pricing, claims management, underwriting, and predictive health, using Python, PyTorch/JAX, and causal inference methods.
The Founding Senior Data Scientist will build and deploy machine learning models for banking products while establishing the company's ML infrastructure, evaluation frameworks, and production standards. The role requires a hybrid practitioner comfortable with both model development and the underlying systems architecture using tools like Python, Snowflake, and Kubernetes.
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