Applied Scientist Ii
2 months ago
Microsoft AI (MAI) org is accelerating innovation to enable truly intelligent web experience products for every person. As part of the Trustworthy Fundamentals team, we focus on keeping Web and Bing safe for our customers. Doing this at web-scale impacts billions of queries per day and millions of users through state-of-the-art deep-learnt models. If you are excited and passionate about building SOTA models, running end to end experiments and creating substantial impact, you will find a home in our team.
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**:
- Ability to conceptualize, design and build an efficient data pipeline that can train, test and deploy high quality models into production to run at scale.
- Communicate with technical and non-technical audiences and contribute modelling expertise as a team player.
**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 field
- OR equivalent experience.
- 3+ years of industry work experience in Python, SQL, R, machine/deep learning, and analysis (Recommenders, Prediction, Classification, Clustering, etc.) in big data environment.
**Preferred Qualficications**:
- Experience with programming, e.g. Java, C#.
- Experience on large scale computing systems like COSMOS, Hadoop, MapReduce and/or similar systems.
- Familiarity with deep learning toolkits like - PyTorch, TensorFlow, etc.
- Self-driven and ability to deliver ambiguous projects with incomplete or dirty data.
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