Applied Scientist III

InMobi•San Mateo, CA

18d

About The Position

We are looking for an Applied Scientist III to join our algorithmic and research science team. You’ll work on mathematically rigorous, research-driven problems at production scale. 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. 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. 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.

Requirements

Ph.D. (preferred) or Master’s degree in Computer Science, Statistics, Mathematics, Operations Research, Physics, or a related quantitative discipline.
5.5–7 years of experience working on algorithmic or applied research problems, ideally with some production deployment experience.
Deep grounding in one or more of: Statistical learning theory, optimization, probability theory, and information theory Causal inference, decision theory, game theory Online learning, bandits, RL, Bayesian methods
Proficient in scientific computing with Python, including packages such as NumPy, SciPy, PyTorch, or TensorFlow.
Comfortable working with big data platforms like Apache Spark, distributed computing, and large-scale datasets.
A researcher’s mindset: questions first, implementation later. You are thoughtful about assumptions and rigorous about validation.
End-to-end ownership: you can go from idea to production and thrive in applied settings.

Nice To Haves

Strong publication record (e.g., NeurIPS, ICML, AISTATS, KDD, UAI, WSDM, EC, SODA, COLT) is a strong plus—even if not recent.
Prior experience in ad tech, marketplaces, or dynamic pricing is helpful but not required.

Responsibilities

Formulate, analyze, and implement algorithms that power real-time auctions, dynamic pricing, bid shaping, pacing, and traffic allocation across a massive-scale ad marketplace.
Design and experiment with methods in online learning, reinforcement learning, multi-armed bandits, forecasting, game theory, and Bayesian modeling—in non-stationary, adversarial environments.
Collaborate with product and engineering teams to deploy your models in production and run real-world experiments with rapid feedback loops (measured in hours, not weeks).
Contribute to the scientific community by publishing high-quality research, conducting internal seminars, and staying abreast of advances in machine learning, algorithms, and applied statistics.
Evaluate the long-term dynamics of deployed algorithms, incorporating feedback, exploitation-exploration trade-offs, and incentives within multi-agent systems.
Identify new areas for innovation by translating business challenges into research questions and proposing novel, high-impact methodologies.
Translate mathematical ideas into practical, high-performance algorithms that operate at scale in production environments.
Explore and close the loop between model predictions and real-world outcomes, refining algorithms based on system behavior.

Benefits

Competitive salary and RSU grant (where applicable)
High-quality medical, dental, and vision insurance (including company-matched HSA)
401(k) company match
Generous combination of vacation time, sick days, special occasion time, and company-wide holidays
Substantial maternity and paternity leave benefits and compassionate work environment
Flexible working hours to suit everyone
Wellness stipend for a healthier you!
Free lunch is provided in our offices daily
Pet-friendly work environment and robust pet insurance policy - because we love our animals!
LinkedIn Learning on demand for personal and professional development
Employee Assistance Program (EAP)