Staff Applied Scientist I

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InMobi Advertising is a global technology leader helping marketers win the moments that matter. Our advertising platform reaches over 2 billion people across 150+ countries and turns real-time context into business outcomes, delivering results grounded in privacy-first principles. Trusted by 30,000+ brands and leading publishers, InMobi is where intelligence, creativity, and accountability converge. By combining lock screens, apps, TVs, and the open web with AI and machine learning, we deliver receptive attention, precise personalization, and measurable impact. Through Glance AI, we are shaping AI Commerce, reimagining the future of e-commerce with inspiration-led discovery and shopping. Designed to seamlessly integrate into everyday consumer technology, Glance AI transforms every screen into a gateway for instant, personal, and joyful discovery. Spanning diverse categories such as fashion, beauty, travel, accessories, home décor, pets, and beyond, Glance AI delivers deeply personalized shopping experiences. With rich first-party data and unparalleled consumer access, it harnesses InMobi's global scale, insights, and targeting capabilities to create high impact, performance driven shopping journeys for brands worldwide. Recognized as a Great Place to Work, and by MIT Technology Review, Fast Company's Top 10 Innovators, and more, InMobi is a workplace where bold ideas create global impact. Backed by investors including SoftBank, Kleiner Perkins, and Sherpalo Ventures, InMobi has offices across San Mateo, New York, London, Singapore, Tokyo, Seoul, Jakarta, Bengaluru and beyond. At InMobi Advertising , you'll have the opportunity to shape how billions of users connect with content, commerce, and brands worldwide. To learn more, visit www.inmobi.com Position Summary: We look for talented Applied Scientists who can roll up their sleeves and have direct impact on our company metrics. The performance of our models and experiments are seen astonishingly quickly - the learning loop is not measured in weeks or days, but hours and minutes. We live in what might be the fastest model-learning playgrounds in the world. We have built an infrastructure that enables model deployment at both scale and speed. As data scientists, we sit alongside engineering colleagues who enable our models to deploy. Combine this with our growing variable set of hundreds of potential features (and growing!), and this is a highly fertile environment for building, experimenting, refining and achieving real impact from your models. If models fire, the bottom-line impact to our teams is immediate - you see the value of your work incredibly fast. Who Are You? Our scientists are expected to possess deep expertise and experience in Ad Tech, AI/ML, and Data Science, particularly at scale. Familiarity with big data processing and cloud computing will be critical to succeed in this environment. In addition to possessing a mathematical aptitude (Statistics, Probability Theory, Algorithms, Foundations of Machine Learning), they need to be competent with data science languages and tools, such as Python or Apache Spark; which will enable them to design scalable solutions for our advertising products, implement proof-of-concept, and evaluate them offline and online. They will also need to work with other engineers to take these solutions to live production and drive real business value. Most importantly, we look for a passion to investigate and learn about the world from data, to ask interesting and provocative questions, and be driven to put real models into production that drive real business value. We are open to diverse academic backgrounds, providing an intent to think and problem-solve like a data scientist. Our team includes engineers, mathematicians, computer scientists, physicists, economists and social scientists - a rock-star data scientist can come from any academic field. Required: Master's in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research or Economics, Analytics, Data Science. Or Bachelor's from a reputed College with additional experience. 7-10 years of work experience in a quantitative field, with model building and validation experience. Ad tech related industry experience is a plus. There, you would have applied algorithms and techniques from Machine Learning, Deep Learning and Statistics or other domains in solving real world problems and understand the practical issues of using these algorithms especially on large datasets. Comfortable with software programming and statistical platforms such as R, Python etc. including visualization tools. Comfortable with the big data ecosystem and Apache Spark. Familiarity with Microsoft Azure, AWS, or Google Cloud/Vertex AI will be a bonus. Comfortable collaborating with cross-functional teams. Familiarity with challenges of the identity-less world, particularly for iOS and Android Excellent technical and business c

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