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
Overview Of The Role
We are looking for a Staff Applied Scientist I to join our algorithmic and research science team. You'll work on mathematically rigorous, research-driven problems at production scale, while also shaping the direction of key initiatives and mentoring other scientists. This role sits at the intersection of theory and application, designing algorithms that combine elegant modeling with measurable business impact. Specifically, our scientists tackle challenges across traffic shaping, fraud detection, ad quality, pricing strategies, and auction theory, along with their practical applications. We leverage the latest deep learning models alongside classical machine learning techniques to build innovative solutions.
As the heart of the InMobi Exchange, our team optimizes the company's core business functions and creates the strategic moat that sets us apart in the market. As a Staff Scientist, you will not just 'use models'—you will formulate them, evaluate their assumptions, tailor them to our problem domain, and bring them to life in production—while providing thought leadership to the broader team. Many of our challenges have no off-the-shelf solutions; we require scientific creativity to bridge research and reality.
If you thrive on solving complex, high-impact problems and want to see your ideas shape the future of a global exchange, this is the place where your work will truly make a difference.
The Impact You'll Make
The Experience We Need
The InMobi Culture
At InMobi, culture isn't a buzzword; it's an ethos woven by every InMobian, reflecting our diverse backgrounds and experiences.
We thrive on challenges and seize every opportunity for growth. Our core values — thinking big, being passionate, showing accountability, and taking ownership with freedom — guide us in every decision we make.
We believe in nurturing and investing in your development through continuous learning and career progression with our InMobi Live Your Potential program.
InMobi is proud to be an Equal Employment Opportunity employer and is committed to providing reasonable accommodations to qualified individuals with disabilities throughout the hiring process and in the workplace.
Visit https : / / www.inmobi.com / company / careers to better understand our benefits, values, and more!
Skills Required
causal inference , Scipy, reinforcement learning, probability theory, Apache Spark, game theory, online learning , Tensorflow, Numpy, Pytorch, Bayesian Methods, decision theory , information theory, Python
Data Scientist • India, Bengaluru / Bangalore