Data & Applied Scientist

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

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.
We are the computational advertising team in the AI & Research organization at Microsoft. We are looking for candidates with research and applied experience in machine learning related areas. Search advertising is a $100 billion market worldwide. Microsoft's Bing search engine supports over 30% of desktop search in the US, with similarly significant presence in many other countries.

We are a team of applied scientists working on machine learning components in the whole sponsored search stack. Our team works on problems related to machine learning, deep learning, natural language processing, image understanding, optimization, information retrieval, auction theory, among others. Our work entails building large-scale machine learning systems for ad matching, filtration, ranking, and multiobjective optimization, and a number of other ML-driven business problems. You will design, implement, analyze, tune complex algorithms and ML systems and the supporting infrastructure for operating on large datasets. You will collaborate with top machine learning scientists and engineers in delivering direct business impact. We're looking for sound understanding and insight into productionizing machine learning models in large-scale systems, an ability to pick up new technical areas, as well as a commitment to developing, delivering, and supporting algorithms in production.

Responsibilities

• Develop novel algorithms in the space of sponsored search to constantly improve the operational efficacy and monetization impact to stake holders
• Analyze Giga/Tera bytes 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 stake holders

Qualifications

• MS/BS in CS/EE, mathematical or machine learning related disciplines, with 3 or more years of experience
• Solid understanding of probability, statistics, machine learning, data science
• A/B testing & analysis of ML models, and optimizing models for accuracy
• Experience with Hadoop, Spark, or other distributed computing systems for large-scale training & prediction with ML models.
• End-to-end system design: data analysis, feature engineering, technique selection & implementation, debugging, and maintenance in production.
• Experience implementing machine learning algorithms or research papers from scratch

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, 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/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.