Microsoft Off Campus Drive 2024 Hiring for Data Scientist
Microsoft Off Campus Drive 2024: Join Microsoft’s Off Campus Drive in 2024 and ignite your career as a Data Scientist. At Microsoft, a global technology leader, you’ll have the opportunity to leverage cutting-edge technologies, analyze vast datasets, and derive actionable insights to drive innovation. As a Data Scientist, you’ll collaborate with diverse teams, tackle complex challenges, and shape the future of data-driven decision-making. Don’t miss this chance to be part of Microsoft’s mission to empower every person and organization on the planet to achieve more.
Company Name: Microsoft
Website: Microsoft
Job Role: Data Scientist
Qualification: B.E/B.Tech
Passout Year: 2023/2024
Job Location: Multiple Locations
Salary: Best In Industry
Experience Level: 0 – 1 Year
Job overview Of Microsoft Off Campus Drive 2024:
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-all’s 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. 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. Come build community, explore your passions, and do your best work at Microsoft with thousands of university graduates from every corner of the world.
Required/Minimum Qualifications
- Bachelor’s Degree in Data Science, Mathematics, Statistics, Computer Science, or related field
- OR equivalent experience.
Job Responsibilities:
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. Contributes 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 in order to identify quality problems, discover insights into the data, and/or detect subsets to form hypotheses. Understands 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
- Understands linkage between 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 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. Contributes to the development, testing, and implementation of changes to optimize code and improve reliability of systems/solutions. Develops an understanding of proper debugging techniques such as locating, isolating, and resolving errors and/or defects. Understands known issues and learns from senior developers/team members. Develops foundational understanding of Agile methodology and when they 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. Understands 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 interpret results, develops insights, and communicates results to customers. Possesses basic understanding about model accuracy dependency on data quality and able to articulate it in customer discussions.
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