Data and Applied Scientist

Job Description

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 billion 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 information retrieval, data mining, machine learning, statistical modelling, optimization, linear algebra, and micro-economics, to solve challenging problems that arise in online advertising.  

We need candidates who have successfully shipped machine learning-based solutions and have 6+ years of relevant academic or research experience. This is a rare opportunity to influence technology development in an important growth area at Microsoft.  You will design, implement, analyze and tune complex algorithms and ML models operating on large datasets in collaboration with top scientists and engineers across Microsoft’s global R&D team.

Responsibilities

• Develop novel algorithms in the space of sponsored search to constantly improve the operational efficacy and monetization impact on stakeholders  
• Analyze Giga/Terabytes of logs and create observation/opportunities and avenues of improvements in the system 
• Identify and apply machine learning solutions at various aspects of the system stack 
•  Monitor for alerts and root cause the live/off-line aspects for any abnormalities in the system  
• Ideate on newer aspects of advertising avenues and augment the platform with richer products for the stakeholders 

Qualifications

• PhD/MS in Computer science or related areas with a strong inclination towards learning algorithms is preferred 
• Strong foundations in the mathematical aspects of learning including optimization, linear algebra & statistical modelling 
• Hands-on experience in feature engineering and building scalable machine learning algorithms  
• Experience in web-search/sponsored-search domains is a plus 
• Excellent problem-solving capabilities with strong fundamentals in computer science 
• Strong software design and development skills in one or more high-level languages (C#/C/C++/Java/F# etc) 
• Knowledge in at least one scripting language (Python, Perl, Ruby, etc) is a plus 
• Proficiency in distributed computing tools like MapReduce/MPI (Cosmos/Hadoop/Spark/Hive etc) is a plus 

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, colour, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits and Perks

The benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

• Industry-leading healthcare
• Savings and investments
• Giving programs
• Educational resources
• Maternity and paternity leave
• Opportunities to network and connect
• Discounts on products and services
• Generous time away