What if your job description were simply “make tomorrow better?” Every day at Microsoft, we bring an insatiable curiosity to the workplace, challenging ourselves to reimagine what it is and what it can be. We build on what’s come before to create what’s next. We help shape the future and we empower billions of people around the globe.
Online Advertising is one of the fastest growing businesses on the Internet today, with about $70 billions of a $600 billion advertising market already online. Search engines, web publishers, major ad networks, and ad exchanges are now serving billions of ad impressions per day and generating terabytes of user events data every day. The rapid growth of online advertising has created enormous opportunities as well as technical challenges that demand computationally intelligent and scalable algorithms. Eventually Computational Advertising has emerged as a new interdisciplinary field that involves complex software engineering, system design, information retrieval, data mining, machine learning, statistical modeling, optimization, linear algebra, and micro-economics, to solve challenging problems that arise in online advertising.
We are looking for Senior Applied Scientist with expertise in areas like Machine Learning, Reinforcement Learning, Causal Inference to join our team at Microsoft Ads India. This role offers a unique opportunity to work on some of the most complex and high-impact challenges in online advertising, where your innovations will directly shape user experience, advertiser success, and the future of the digital advertising ecosystem. We need people who have trained and shipped large scale production models and have 7 or more years of relevant applied science experience. In this team, you will be working on the highly reliable online auction simulation platform and demand intelligence - Microsoft AdInsights that empowers advertisers to optimize their campaigns. You will analyze large amount of advertiser data, improve existing models and extract insights that advertiser can take action on. Excellent machine learning and causal inference skills are needed for this role. This is part of the core auction engine team that drives money for Microsoft while ensures best experience for users and advertiser ROI. This is a rare opportunity to influence technology development in an important growth area at Microsoft. You will work towards empowering the demand/advertisers to be intelligent in collaboration with top scientists and engineers across Microsoft’s global R&D team and improve the long term health of the ads ecosystem in Microsoft.
Responsibilities
- Drive AI innovation: Lead the development of cutting-edge models that select and rank ads, predict user interaction given a specific context, model clicks for each campaign, and optimize advertiser outcomes. You will leverage advance Deep Learning, Reinforcement Learning, Causal Inference, and other techniques to solve complex problems.
- Optimize at scale: Design, build, and deploy models that operate at web scale, ensuring they are robust, scalable, and high performing in real-world settings. You will directly improve user engagement, ad relevance, and advertiser return on.
- Perform large-scale online and offline experiments to continuously optimize and validate model performance, ensuring real-time impact on user and advertiser experiences.
- Work closely with worldwide research, engineers, data scientists, and product teams to integrate your solutions into Microsoft Ads systems, driving cross-team collaboration and delivering impactful end-to-end solutions.
Qualifications
Required/Minimum Qualifications:
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics predictive analytics, research).
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research).
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ year(s) related experience (e.g., statistics, predictive analytics, research).
- OR equivalent experience.
- Experience with large-scale models and frameworks such as PyTorch/Tensor flow.
- Python, C#, Java or other OOPs programing language.
- Technical expertise and working experience on Deep Learning, Reinforcement Learning, Causal Inference.
- Experience building, deploying, and optimizing large-scale AI/ML models in real-world applications.
- Publications in top-tier conferences like NeurIPS, ICML, CVPR, SIGIR, KDD, ACL, EMNLP, ICLR, WWW, WSDM or similar, demonstrating expertise in advancing the field - would be preferred.
- Masters / PhD in Machine Learning, AI, or related fields.
- Background in developing or modifying deep learning algorithms/architectures to improve computational and memory efficiency.
- Experience in online advertising, search engines, or recommendation systems.
Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
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This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
Skills Required
- Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field, plus 8+ years of related experience; or master's degree plus 6+ years; or doctorate plus 4+ years; or equivalent experience.
- Experience with large-scale models and frameworks such as PyTorch or TensorFlow.
- Programming experience in Python, C#, Java, or another object-oriented programming language.
- Technical expertise and professional experience in deep learning, reinforcement learning, and causal inference.
- Experience building, deploying, and optimizing large-scale AI or machine learning models in real-world applications.
- Background in developing or modifying deep learning algorithms or architectures to improve computational and memory efficiency.
- Experience in online advertising, search engines, or recommendation systems.
- Publications in top-tier conferences such as NeurIPS, ICML, CVPR, SIGIR, KDD, ACL, EMNLP, ICLR, WWW, or WSDM.
- Master's or PhD in Machine Learning, Artificial Intelligence, or a related field.
- Ability to meet Microsoft, customer, and/or government security screening requirements, including the Microsoft Cloud Background Check.
Microsoft Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.
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Fair & Transparent Compensation — Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
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Retirement Support — Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
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Parental & Family Support — Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.
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