Applied Scientist III

Inmobi
Bengaluru
Workplace: OnsiteFull timeFunction: Research & Scientific (R&D)Experience: 4-7 yearsEducation: phdSkills: ["Researcher's mindset","Rigorous validation","End-to-end ownership","Thoughtful about assumptions","Scientific creativity"]

Own end-to-end research and algorithm development for a massive ad marketplace, translating business challenges into production-ready methods. Build and evaluate real-time auction and dynamic pricing systems using online learning, reinforcement learning, multi-armed bandits, forecasting, game theory, and Bayesian modeling in non-stationary environments. Partner with product and engineering to deploy models, run fast experiments, and raise the team’s scientific rigor through reviews, publications, and internal seminars.

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FursaFursa
Inmobi
Inmobi
1 day ago

Applied Scientist III

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Job Summary

Own end-to-end research and algorithm development for a massive ad marketplace, translating business challenges into production-ready methods. Build and evaluate real-time auction and dynamic pricing systems using online learning, reinforcement learning, multi-armed bandits, forecasting, game theory, and Bayesian modeling in non-stationary environments. Partner with product and engineering to deploy models, run fast experiments, and raise the team’s scientific rigor through reviews, publications, and internal seminars.
Location: Bengaluru
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Mid level

Key Responsibilities

  • •Formulate, analyze, and implement algorithms powering real-time auctions, dynamic pricing, bid shaping, pacing, and traffic allocation in an ad marketplace.
  • •Design and experiment with online learning, reinforcement learning, multi-armed bandits, forecasting, game theory, and Bayesian modeling in non-stationary, adversarial environments.
  • •Collaborate with product and engineering to deploy models in production and run real-world experiments with rapid feedback loops.
  • •Evaluate long-term dynamics of deployed algorithms, including feedback, exploitation–exploration trade-offs, and incentives in multi-agent systems.
  • •Translate business challenges into research questions and drive the loop from model predictions to real-world outcomes, refining algorithms based on system behavior.

Key Requirements

  • •Ph.D. in Computer Science, Statistics, Mathematics, Operations Research, Physics, or a related quantitative field (degree not strictly required if you show research depth and production impact).
  • •4–7 years of experience in algorithmic or applied research problems, including significant production deployment experience.
  • •Strong grounding in statistical learning theory, mathematical optimization, probability theory, and/or information theory.
  • •Experience with causal inference, decision theory, game theory, and/or auction theory; plus online learning, bandits, RL, and/or Bayesian methods.
  • •Proficiency in scientific computing with Python and comfort working with big data platforms such as Apache Spark and large-scale datasets.
Experience:4-7 yearsAd techMarketplaces
Education:PhD / Doctorate in Computer Science, Statistics, Mathematics, Operations Research, Physics, or a related quantitative discipline
Skills:Researcher's mindsetRigorous validationEnd-to-end ownershipThoughtful about assumptionsScientific creativity
Tech Stack:PythonNumPySciPyPyTorchTensorFlowApache Spark

Company Brief

Inmobi
InMobi is a global mobile advertising and discovery platform that helps brands and app developers reach and engage audiences through programmatic advertising, monetization solutions, and data-driven targeting across mobile devices.
Industry: Advertising Media Groups
Company Size: Enterprise (1,001+ employees)
Growth: Established Company
Funding: Series E+
Headquarters: Bengaluru, India
Founded: 2007
WebsiteLinkedIn