Senior Data Scientist

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Company Overview

A leading global payments and technology organization is advancing digital commerce through secure, accessible, and innovative payment solutions. Its technology, partnerships, and global networks support individuals, businesses, and governments across more than 200 countries and territories while enabling data-driven products and services that contribute to a more sustainable and inclusive digital economy.

The organization is seeking a Senior Data Scientist to design, develop, and deploy machine learning models that power ad targeting, ranking, and bidding optimization in real-time and near real-time environments. The role will contribute to advancing commerce media and AdTech capabilities through data-driven personalization, measurement, and optimization solutions.

The successful candidate will work across data science, engineering, product, analytics, and business functions to develop scalable solutions using large-scale transaction and behavioral datasets. The role requires strong expertise in machine learning, experimentation, causal inference, attribution modeling, and digital advertising technologies.

Key Responsibilities

• Design, build, and deploy machine learning models for ad targeting, ranking, and bidding optimization.
• Develop and scale personalization and recommendation systems using large-scale transaction and behavioral datasets.
• Lead the design and implementation of incrementality testing frameworks, including lift measurement and causal inference methodologies, to evaluate campaign effectiveness.
• Build and enhance attribution models, including multi-touch and probabilistic attribution approaches across channels and devices.
• Partner closely with product, engineering, analytics, and business teams to translate business objectives into scalable data science solutions.
• Optimize machine learning models for accuracy, performance, latency, and scalability in production environments.
• Contribute to the architecture, design, and evolution of AdTech and commerce media products.
• Drive experimentation strategies, including A/B testing and advanced measurement frameworks.
• Stay current with emerging trends and technologies across the AdTech ecosystem, including DSPs, SSPs, RTB protocols, identity resolution, privacy-preserving techniques, and digital advertising measurement.

Required Qualifications

• Experience in Data Science, Machine Learning, AdTech, Marketing Science, or a related field.
• Proven experience building and optimizing ad bidding systems, including RTB optimization, budget pacing, bid shading, and auction-based decision-making.
• Hands-on expertise developing personalization, recommendation, and targeting systems at scale.
• Strong background in incrementality measurement, experimentation, A/B testing, causal inference, and advanced attribution modeling.
• Deep understanding of the digital advertising ecosystem, including DSPs, SSPs, ad exchanges, identity solutions, targeting strategies, and measurement methodologies.
• Proficiency in Python and related data science libraries, with strong experience in data manipulation, feature engineering, and model development.
• Experience working with large-scale distributed data processing frameworks such as Apache Spark.
• Demonstrated success deploying machine learning models into production environments, including batch and real-time pipelines, APIs, monitoring, and model lifecycle management.
• Strong foundation in statistics, machine learning algorithms, optimization techniques, and predictive modeling.
• Experience leveraging cloud platforms such as AWS, Azure, or GCP, along with modern ML infrastructure and MLOps tools.
• Excellent communication and stakeholder management skills, with the ability to explain complex analytical concepts to both technical and non-technical audiences.
• Ability to thrive in a fast-paced, highly collaborative environment and influence both technical and business stakeholders.

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