On-site opportunity at
InMobiApplied Scientist III
This full-time, on-site Applied Scientist III role is based in San Mateo, CA, within InMobi's algorithmic and research science group, which works on the core of…
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About This Role
This full-time, on-site Applied Scientist III role is based in San Mateo, CA, within InMobi's algorithmic and research science group, which works on the core of the InMobi Exchange. Current topics span traffic shaping, fraud spotting, ad quality, price strategy and auction theory. The work joins mathematically careful modelling with production systems that run at very large scale, and the team regards its optimization as a key source of advantage…
Job Description
This full-time, on-site Applied Scientist III role is based in San Mateo, CA, within InMobi's algorithmic and research science group, which works on the core of the InMobi Exchange. Current topics span traffic shaping, fraud spotting, ad quality, price strategy and auction theory. The work joins mathematically careful modelling with production systems that run at very large scale, and the team regards its optimization as a key source of advantage in the market.
The scientist develops and tests algorithms that drive live auctions, price setting, bid adjustment, budget pacing and traffic routing. Techniques named include Bayesian modelling, bandit algorithms, forecasting, game theory, online learning and reinforcement learning, used where conditions move constantly and opponents may act strategically. Experiments run on feedback cycles of hours rather than weeks, and models are deployed alongside product and engineering colleagues.
Beyond shipping models, the scientist studies how deployed algorithms behave over the long run, including feedback loops, the balance between exploring and exploiting, and incentives in systems with many agents. The role turns business questions into research problems, publishes strong work, runs internal seminars and keeps pace with developments in machine learning and applied statistics. It suits people who enjoy prototyping and seeing their ideas reach production.
Applicants ideally hold a PhD, though a master's in a quantitative field such as physics, operations research, statistics, math or computer science is also acceptable. Several years of algorithmic or applied research experience, ideally including production deployment, are expected, along with solid grounding in statistical learning, optimization, probability, causal inference, decision theory, bandits, reinforcement learning or Bayesian methods. Python skills with NumPy, SciPy, PyTorch or TensorFlow, and familiarity with Spark, are needed. The fixed base range is $148,200 to $216,500 USD for the California and New York offices.
Responsibilities
- Devise, analyse and ship algorithms for real-time auctions, price setting, bid shaping, pacing and traffic routing
- Prototype and evaluate approaches built on bandits, Bayesian modelling, forecasting, game theory, online learning or reinforcement learning
- Work with product and engineering colleagues to put models into service and run experiments on live traffic
- Assess the long-run behaviour of deployed algorithms, including incentives among interacting agents
- Turn commercial problems into research questions and suggest novel techniques
- Publish research, host internal seminars and follow developments in machine learning and applied statistics
- Refine algorithms using feedback from how the live system behaves
Requirements
- Master's or PhD in physics, operations research, statistics, math or computer science, or a closely related quantitative subject
- Several years of algorithmic or applied research work, ideally including production deployment
- Solid grounding in statistical learning, optimization, probability or information theory
- Working knowledge of causal inference, decision theory or game theory, or of bandits, reinforcement learning or Bayesian methods
- Proficiency in Python scientific computing with NumPy, SciPy, PyTorch or TensorFlow
- Comfort with big data platforms such as Apache Spark
Qualifications
- Papers at venues such as NeurIPS, ICML, AISTATS, KDD, UAI, WSDM, EC, SODA or COLT count in your favour
- Background in ad tech, marketplaces or price optimization helps, though it is optional
Core Skills
Benefits
- Base pay and an ESOP grant where eligible
- Health, dental and eye cover, with an HSA contribution from the employer
- Retirement plan with employer matching
- Paid time off, sick leave, leave for special occasions and company holidays
- Parental leave for both maternity and paternity
- Adjustable hours and a wellness allowance
- Free lunch at the office each day, pet insurance and an employee assistance programme
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Where is this job based?
The role is on-site in San Mateo, CA, according to the posting.
What education is preferred?
A PhD is preferred. A master's in physics, operations research, statistics, math or computer science is also accepted, as is a closely related quantitative degree.
What is the base salary?
The posting gives a fixed base range of $148,200 to $216,500 USD for the California and New York offices.
Is the role full-time?
Yes. The listing is full-time and on-site.
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