Principal Applied Scientist

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, among others. Our work entails building large-scale machine learning systems for user response modelling, ranking, and a number of other ML-driven business problems. The **Principal Applied Scientist** will design, implement, analyze, tune complex algorithms and ML systems and the supporting infrastructure for operating on large datasets. They 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

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.

**Responsibilities**:

- You will master one or more subareas and gain expertise in a broad area of research. You’ll use your expertise to identify appropriate techniques for examining a problem and foster an audience for the product based on your understanding of the industry.
- You will review business and product requirements, identify problems, and develop strategies to resolve team problems.
- You’ll develop an understanding of tools and methods being used in the community and hold team members accountable to support business impact.
- You will share industry and competitive insights and build capabilities through coaching. You’ll provide guidance around best practices and collaborate with the academic community to develop the recruiting pipeline.
- You will document scientific work to ensure processes are captured. You’ll also contribute to ethics and privacy policies related to research processes by providing updates and suggestions around best practices.

**Qualifications**:
**Required Qualifications**:

- Bachelor'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 Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent 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.
- Experience with 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
- Solid experience with TensorFlow/PyTorch and deep learning models is a prerequisite.

**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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