Applied Scientist

Overview

The Product Ads Algorithm & Infrastructure team in Ads Understanding team is hiring an Applied Scientist for our Vancouver, British Columbia, Canada location. The team is responsible for product ads selection, relevance, modeling, and online infrastructure for serving and experimenting cutting edge algorithms, ranging from natural language processing (NLP) to information retrieval, computer vision, etc. The team leverages heavily on deep learning methodologies to build solutions to meet the Commerce Strategy of Microsoft, where Product Ads is at the center of it! We are looking for a passionate scientist to deliver an amazing shopping experience with our multi-modal models backing it up.

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. Rapid online advertising growth has created enormous opportunities and technical challenges that demand computational intelligence. Computational Advertising has emerged as a new interdisciplinary field that involves information retrieval, machine learning, data mining, statistics, operations research, and micro-economics, to solve challenging problems that arise in online advertising. The central problem of computational advertising is to select an optimized slate of eligible ads for a user to maximize a total utility function that captures the expected revenue, user experience and return on investment for advertisers. Microsoft is innovating rapidly in this space to grow its share of this market by providing the advertising industry with the state-of-the-art online advertising platform and service. Microsoft Ads Relevance and Revenue (RnR) team is at the core of this effort, responsible for research & development of all the algorithmic components in our advertising technology stack.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Qualifications

Required Qualifications :

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ 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 1+ year(s) related experience (e.g., statistics, predictive analytics, research)OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related fieldOR equivalent experience.
• 2+ years working experience in statistical natural language processing (NLP) with latest deep learning technologies including transformer and Large Language Models (LLMs)OR Computer Vision (CV) with latest deep learning technologies including Vision Transformers.
• 2+ years working experience with coding in production systems using c++, c#, jaya or python

Preferred Qualifications :

Applied Sciences IC3 - The typical base pay range for this role across Canada is CAD $83,600 - CAD $159,600 per year.

Find additional pay information here :

Microsoft will accept applications for the role until July 16, 2024

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Responsibilities

Benefits / perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.Industry leading healthcareEducational resourcesDiscounts on products and servicesSavings and investmentsMaternity and paternity leaveGenerous time awayGiving programsOpportunities to network and connect