Data Scientist II

Inmobi

2 - 6 years

14 - 19 Lacs

bengaluru

Posted:6 hours ago| Platform:

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Skills Required

computer science san mobile marketing accessories operations research prototype publishing machine learning forecasting python

Work Mode

Work from Office

Job Type

Full Time

Job Description

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.

The Experience We Need

Ph.D./Master s/Bachelors degree in Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research, Physics, or a related quantitative discipline.
2 6 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
Machine learning, deep learning, reinforcement learning
Online learning, Bayesian methods

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

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