Data Scientist
Bangalore, Karnataka, India
- Date posted Jul 09, 2024
- Job number 1714375
- Work site Up to 100% work from home
- Travel 0-25 %
- Role type Individual Contributor
- Profession Research, Applied, & Data Sciences
- Discipline Data Science
- Employment type Full-Time
Overview
Have you ever imagined a world with an infinite amount of storage available and accessible to everyone? A place where everyone in the world can easily access their data from anywhere at any time via any means (e.g., mobile phones, tablets, PCs, smart devices, etc.). Did you ever desire a universally accessible storage system to record all the knowledge known to mankind or to store all the data collected from all the scientists in the world for them to collaborate upon? Do you want to be part of a team that strives to bring these to reality?
If so, the Microsoft Azure Storage team is what you are looking for. We are building Microsoft’s cloud storage solution – Microsoft Azure Storage, which is a massively scalable, highly distributed, ubiquitously accessible storage system, designed to scale out and serve the entire world. We continue to have tremendous hockey stick growth, we have many Exabyte’s of data stored, and are designing and building systems for Zettabyte scale to support demand growth for the coming years.
As a Data Scientist in the Azure Storage team, you will work on huge amount of data to develop Machine Learning solutions and provide insights to team and customers to make data driven decision. Additionally, you will work closely with engineering teams, product managers, business leaders to build data pipelines, and bring intelligence into the storage service. This opportunity will allow you to gain experience in Big Data, Machine Learning and Distributed Systems in cloud services and storage, accelerate career growth, and provide an opportunity to work in a highly dynamic, flexible, and globally distributed 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
- Assists with initial data collection and understands which analysis techniques appropriate and which tools are necessary for data exploration. Develops a foundational understanding of methodology and standard statistical options to analyze and organize data as required.
- Work with large, complex data sets, solving difficult, non-routine analysis problems with advanced data science methods.
- Applies (or develops if necessary) tools and pipelines to efficiently collect, clean, and prepare massive volumes of data for analysis.
- Transforms problems into analysis plans for data telemetry, metrics, predictive modeling, reporting, and experimentation. Communicates and gets alignment on analytics priorities.
- Work across engineering and product teams to enable metrics for product success.
- Understands modeling techniques used within the team, then run model tools on prepared data sets.
- Supports identification of dependencies, and the development of design documents for a product feature with oversight.
- Create and implement code for a product, service, or feature reusing code as applicable.
Qualifications
Required Qualifications:
- Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
- OR equivalent experience.
- 1+ year(s) customer-facing, project-delivery experience, professional services, and/or consulting experience.
- 1+ year(s) of experience in querying with traditional and big data repositories (MS SQL server, SQL Analysis Service, Azure SQL DB/Data Warehouse, Azure Kusto, MS Fabric/Synpase).
Other Qualifications:
- 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.
Preferred Qualifications:
- Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR equivalent experience.
- Foundation of statistical modeling, machine learning algorithms and experimental design.
- Data visualization skills to be able to present insights that drive business impact.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Industry leading healthcare
Educational resources
Discounts on products and services
Savings and investments
Maternity and paternity leave
Generous time away
Giving programs
Opportunities to network and connect
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