Microsoft Hiring For Data Science | Apply Now

Data Science freshers are being hired by Microsoft Careers in 2024. a bachelor’s degree in computer science, mathematics, statistics, data science, or a related discipline OR comparable work experience. Below is a thorough explanation of the eligibility and application process.

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About Microsoft

The American multinational technology company Microsoft Corporation has its main office in Redmond, Washington. The Microsoft 365 suite of productivity apps, the Edge web browser, and the Windows operating system family are among the company’s best-known software offerings. The Microsoft Surface line of touchscreen personal computers and Xbox game consoles are the company’s main hardware offerings. In the Fortune 500 list of the biggest American companies by total revenue for 2022, Microsoft came in at number 14 and was, as of that year, the largest software maker globally. Together with Amazon, Apple, Facebook’s parent firm Meta, Alphabet (the parent company of Google), and Apple, it is regarded as one of the Big Five American IT businesses.

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Microsoft Hiring For Data Science Details

Job Role: Data Science

Company Website: www.microsoft.com

Qualification: Bachelor’s Degree in Data Science, Mathematics, Statistics, Computer Science, or related field OR equivalent experience

Experience: Fresher

Batch: Recent Batches

Salary: ₹13-₹28 LPA

Job Location: Multiple Locations (Up to 50% work from home)

Last Date: ASAP

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Roles & Responsibilities

• Learns and comprehends the needs and objectives of the project from a business standpoint. helps senior leads evaluate a project’s risks, contingencies, requirements, assumptions, and limitations.
• Participates in the creation of a project plan. shares with stakeholders the insights gained from direct work.
• Helps with initial data gathering and becomes acquainted with the data in order to find patterns in the data, identify issues with quality, and/or find subsets to generate hypotheses.
• Possesses an understanding of the major technologies and tools required for data exploration, such as Python and structured query language (SQL), as well as the analysis techniques applicable for the given data.
• Uses expertise in data analysis to the cleaning, transformation, analysis, integration, and organisation of data to the degree necessary for the chosen analysis approaches. Aids in the description and investigation of data.
• Acquires knowledge and comprehension of the several modelling approaches that the team uses (e.g., support machines, derivatives, neural network formation, decision-tree building, multiple regression, and linear regression).
• Creates one or more models by running model tools on a prepared dataset and asking for help as necessary. Contributes to the development of machine learning (ML) and artificial intelligence (AI) techniques and algorithms through research, identification, prototyping, and productization.
• Works in tandem with development engineers and project managers to create features for the product that are powered by AI and machine learning.
• Recognises the relationship between the achieved model and the company’s goals. helps with testing models using real or production data, test apps, and test data.
• Evaluate the function of the model. Integrates both explicit and implicit user feedback into the model’s assessment. Reviewing modelling and data analysis methods helps identify potential ignored elements.
• Learns about and comprehends the present status of the industry, including information on the instruments, methods, plans, and procedures that can be used to enhance the effectiveness and efficiency of processes.
• Keeps up with the most recent developments in the field. when necessary, takes part in hands-on training and internal research conferences.
• Actively adds to the corpus of knowledge on intellectual property (IP) best practices and thought leadership.
• Writes legible code for a particular feature, improvement, or model, asking for help as necessary. Participates in the creation, testing, and application of modifications aimed at optimising code and enhancing system/solution reliability.
• Increases knowledge of appropriate debugging methods, including finding, identifying, and fixing mistakes and/or flaws.
• Learns from more experienced coders and team members and comprehends known concerns.
• Increases knowledge of data structures and how Microsoft’s client business is impacted by them. Learns from senior engineers how to spot growth prospects, comprehend strategy goals, goals related to customers and products, and investigates potential for applying machine learning (ML).
• When necessary, seeks advice. Recognises the customer’s business objectives based on the premise of engagement.
• Uses business and data science knowledge to analyse projects with a customer-focused approach. controls client expectations for the timeliness and progress of projects and products. assumes accountability for boosting customer excellence.
• Assists senior team members, gains knowledge from them, generates ideas, interprets results, and conveys results to clients.
• Understands the fundamentals of how data quality affects model accuracy and is able to explain them to customers.

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how to apply for Microsoft Hiring For Data Science

The following link will allow all interested and qualified applicants to apply online for Microsoft Careers 2024 as soon as feasible.