The world craves insights, and data is the key. But raw data is just potential. It’s Microsoft Data Science that unlocks its true power, transforming information into actionable intelligence for businesses worldwide.
Are you a university graduate with a sharp mind and a passion for problem-solving? Do you crave a career at the cutting edge of technology, where your work shapes the future? If so, then a Microsoft Data Science role might be your perfect fit.
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Table of Contents
About the Microsoft
Every year, we welcome thousands of university students from every corner of the world to join Microsoft. You bring your aspirations, talent, potential—and excitement for the journey ahead. We’re a company of learn-it-alls rather than know-it-alls and our culture is centered around embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. Does this sound like you? Learn more about our cultural attributes.
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.
Those hired into this role are invited to participate in Microsoft Aspire Experience, a two-year learning and development experience where you’ll build your network, cultivate intentional capabilities, and gain perspective into the career opportunities across Microsoft’s many exciting businesses.
Come build community, explore your passions, and do your best work at Microsoft with thousands of university graduates from every corner of the world.
Eligibility Criteria
Bachelor’s Degree in Data Science, Mathematics, Statistics, Computer Science, or related field OR equivalent experience.
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Role and Resposnibility
Business Understanding and Impact
Learns and understands project objectives and requirements from a business perspective. Assists senior leads with the assessment of a project, including risks, contingencies, requirements, assumptions, and constraints. Contribute to the development of a project plan. Shares insights with stakeholders based on direct work.
Data Preparation and Understanding
Assists with initial data collection and familiarizes self with data to identify quality problems, discover insights into the data, and/or detect subsets to form hypotheses. Understand which analysis techniques are appropriate for data and which key technologies and tools are necessary for data exploration (e.g., structured query language [SQL], Python). Leverages data analysis knowledge to clean, transform, analyze, integrate, and organize data to the level required by the analysis techniques selected. Contributes to the description and exploration of data. Develops foundational understanding of methodology and standard statistical options and when they should be used. Understands and follows ethics and privacy policies when collecting and preparing data. Adheres to Microsoft’s privacy policy related to collecting and preparing data. Identifies data integrity problems.
Modeling and Statistical Analysis
Learns and understands various modeling techniques used within the team (e.g., linear regression, multiple regression, decision-tree building, neural network generation, support machines, derivatives). Runs model tools on prepared dataset to create one or more models, seeking guidance as needed. Contributes to the research, identification, prototyping, and productizing of machine learning (ML)/artificial intelligence (AI) techniques and algorithms. Collaborates with project managers and development engineers to design machine learning and artificial intelligence-driven features in the product.
Evaluating for Insight and Impact
Understand the linkage between the achieved model and business objectives. Assists with testing models on test applications and on real data or production data. Analyzes model performance. Incorporates implicit and explicit customer feedback into model evaluation. Conducts a review of data analysis and modeling techniques to determine factors that may have been overlooked or need to be reexamined. Contributes to the summary of the review process.
Industry and Research Knowledge/Opportunity Identification
Learns and understands the current state of the industry, including knowledge of tools, techniques, strategies, and processes that can be utilized to improve process efficiency and performance. Maintains knowledge of current trends within the discipline. Attends internal research conferences and participates in on-hands training, when appropriate. Actively contributes to the body of thought leadership and intellectual property (IP) best practices.
Coding and Debugging
Writes readable code for a specific feature, enhancement, and/or model, seeking guidance when needed. Contribute to the development, testing, and implementation of changes to optimize code and improve the reliability of systems/solutions. Develops an understanding of proper debugging techniques such as locating, isolating, and resolving errors and/or defects. Understand known issues and learn from senior developers/team members. Develops foundational understanding of Agile methodology and when it should be used. Contributes to documentation for production.
Business Management
Develops understanding of data structures and their relationship to Microsoft’s customer business. Observes senior engineers and learns best practices in identifying growth opportunities, understanding strategy goals, customer- and product-strategy goals, and exploring opportunities for machine learning (ML) application, seeking guidance when needed. Understand the business goals of the customer, per engagement basis.
Customer/Partner Orientation
Leverages understanding of data science and business to examine projects through a customer-oriented focus. Manages customer expectations regarding project/product progress and timeline. Takes responsibility to enhance customer excellence. Assists and learns from senior team members interprets results, develops insights, and communicates results to customers. Possesses a basic understanding of model accuracy dependency on data quality and is able to articulate it in customer discussions.
Benefits of Microsoft Data Science
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
Salary
Monthly in-hand salary: ₹ 2.4 Lakhs – ₹ 2.5 Lakhs
Note: Salary information is taken from here!
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How To Apply?
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