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. Learn more about our cultural attributes . Data Science Full Time Opportunity for University Graduates
- Job number: 1370081
- Date posted : Jul 26, 2022
- Travel: None
- Profession: Engineering
- Role type : Individual
- Contributor Employment type: Full-Time
- Work site: Microsoft on-site only
- Post: Data Science Engineer
- B.Tech / M.Tech/ MS degree in Computer Science or related quantitative field with min. 7/10 CGPA. Batch of 2023. (No backlogs)
- Kaggle score is a plus.
- Experience with R / Matlab / Scipy / Pandas / Weka, and scripting languages such as Perl, Python.
- Experience with Hadoop / Hbase / Pig or Mapreduce / Bigtable / AzureML a plus
- Knowledge of C++, C#, and .NET is a plus.
- Develop highly scalable classifiers, data regression, recommendations and predictive models
- Analyze petabytes of data and mine patterns from logs
- Bring data to life using rich visualizations
- Create language models, speech models, vision models, etc.
- Suggest, collect and synthesize requirements and innovate to create next generation feature sets.
- Enable natural and contextual interactions in apps integrating cognitive and analytics services
- Adapt standard ML methods to best exploit modern parallel environments.
- Implement algorithms that power user and developer-facing products reaching out to millions of users. Measure and optimize the quality of your algorithms.
- Work in product teams shipping large scale end to end applications/solutions.
Interested candidates can apply for this post using the following link https://careers.microsoft.com/us/en/job/1370081/Data-Science-Full-Time-Opportunity-for-University-Graduates?jobsource=linkedin&utm_source=linkedin&utm_medium=linkedin&utm_campaign=linkedin-feed