Data Scientist, Innovation Engineering Technology

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we're hiring: We are expanding our data science capability to develop a state-of-the-art system for estimating and understanding the size and characteristics of marketing and advertising audiences. This role offers the opportunity to apply Bayesian statistics, advanced mathematical thinking and production-quality engineering to complex problems with meaningful industry impact. What You’ll Be Doing Develop and implement Bayesian statistical models and other advanced analytical methods to estimate audience sizes and characteristics. Translate complex mathematical and statistical questions into robust, explainable data-driven solutions. Build and maintain production-ready Python packages, including unit tests and clear technical documentation. Collaborate with data scientists, engineers and other specialists to design, build and refine analytical solutions. Work with diverse data formats and help maintain data quality and integrity throughout the analytics pipeline. Use cloud computing resources to support scalable data processing and model deployment. Contribute to Git repositories, code reviews and

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy. As a Staff Data Scientist, you’ll lead the design and development of scalable ML systems for use cases such as menu recommendation, demand forecasting, offer targeting, and guest personalization. You will serve as a technical thought partner across teams, set best practices, and influence the roadmap for ML-driven products that support key business outcomes. Your work will directly shape strategic decisions and enhance customer experience at scale. A day in the life (Responsibilities) Own the full machine learning lifecycle—from problem framing and data exploration to modeling, deployment, and monitoring—for mission-critical initiatives. Design and implement advanced ML and statistical models that improve product performance, operational efficiency, or customer insights. Collaborate with engineers, product managers, and business stakeholders to define project scope, success metrics, and integration strategy. Guide architectural decisions, set modeling standards, and champion best practices for experimentation, validation, and productionization. Mentor other data scientists and raise the technical bar through design reviews, feedback, and sharing domain expertise. Proactively identify areas where data science can create business value and lead cross-functional efforts to drive those opportunities forward. Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team. What you'll need to thrive (Requirements) 7+ years of experience in data science with a proven track record of delivering production ML systems that drive measurable impact. Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, dee

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy. As a Staff Data Scientist, you’ll lead the design and development of scalable ML systems for use cases such as menu recommendation, demand forecasting, offer targeting, and guest personalization. You will serve as a technical thought partner across teams, set best practices, and influence the roadmap for ML-driven products that support key business outcomes. Your work will directly shape strategic decisions and enhance customer experience at scale. This role is for a current vacancy. A day in the life (Responsibilities) Own the full machine learning lifecycle—from problem framing and data exploration to modeling, deployment, and monitoring—for mission-critical initiatives. Design and implement advanced ML and statistical models that improve product performance, operational efficiency, or customer insights. Collaborate with engineers, product managers, and business stakeholders to define project scope, success metrics, and integration strategy. Guide architectural decisions, set modeling standards, and champion best practices for experimentation, validation, and productionization. Mentor other data scientists and raise the technical bar through design reviews, feedback, and sharing domain expertise. Proactively identify areas where data science can create business value and lead cross-functional efforts to drive those opportunities forward. Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team. What you'll need to thrive (Requirements) 5+ years of experience in data science with a proven track record of delivering production ML systems that drive measurable impact. Deep knowledge of statistical modeling, machine lea

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Data Scientist II Role Overview Build and productionize enterprise-grade AI and Generative AI solutions for Mastercard. This role combines strong software engineering with model fine-tuning, Databricks-based ML engineering, AWS deployment, and end-to-end MLOps. Key Responsibilities Design, develop, test, and maintain scalable AI/ML applications, APIs, and reusable engineering components. Fine-tune and evaluate foundation models using techniques such as LoRA, QLoRA, PEFT, and supervised fine-tuning. Build RAG solutions, embeddings workflows, vector-search applications, and AI agents. Create end-to-end ML pipelines for data preparation, training, evaluation, deployment, monitoring, and retraining. Use Databricks, PySpark, MLflow, Unity Catalog, Workflows, Vector Search, and Model Serving for governed model development and operations. Implement CI/CD, automated testing, observability, model monitoring, and production support practices. Partner with data science, engineering, product, security, privacy, and governance teams to deliver reliable and responsible AI solutions. Required Skills & Experience 3–4 years of experience in AI/ML engineering, software engineering, data science, or a related field. Strong Python, SQL, object-or

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Data Scientist What is the opportunity? We are seeking a highly skilled and motivated Data Scientist to join our Cyber Analytics team within the Security Solutions Data Science organization. This role is critical to driving advanced analytics initiatives, improving fraud detection capabilities, and supporting strategic decision-making across cybersecurity and payment fraud domains. What will you do? • Gain subject matter knowledge on web application security, commonly exploited cyber vulnerabilities, and methods of online and payment card fraud including the common points of purchase for compromised cards. • Build, develop, and maintain innovative data-driven analytical solutions, including predictive models and machine learning algorithms, on large volumes of data to support analytics and reporting needs across products, markets, and services. • Competently handle large datasets, sifting for patterns and trends and translating those insights into technical rules and solutions. • Combine cybersecurity and transaction data into new and insightful views of fraud and vulnerability across the Mastercard network. • Collaborate with cross-functional teams including product, engineering, and operations to understand product, usage, and data pipelines as well as delivering scalable solutions. • T

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Job Summary As a Data Scientist at Micron, you will employ techniques drawn from mathematics, statistics, and information technology to uncover patterns in data, drive predictive models, and develop actionable solutions for advanced semiconductor manufacturing. Your primary focus will be to support Process Integration and Process Engineering teams to enhance product yield and improve process variation. You will interact closely with multi-functional process areas to solve manufacturing line problems and conduct root cause analysis. In this position, you will help develop software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources—such as inline, param, and probe data—translating them into insights that directly improve process capability and device yield. Key Responsibilities Yield & Process Optimization: Collaborate with semiconductor manufacturing engineering teams to analyze inline/param/probe data to identify top yield detractors and drive continuous improvement. Data Pipeline & Automation: Extract, cleanse, and analyze datasets from SQL databases, sensor networks, and fabrication tool logs to support semiconductor manufacturing operati