Microsoft Careers Work from Home Hiring As Data Scientist Internship Role. bachelor’s or master’s degree in engineering, computer science or related field Candidates can apply for the post.
- Company –Microsoft Work From Home
- Role – Data Scientist Internship
- Qualification – bachelor’s or master’s degree in engineering, computer science or related field.
- Experience –1 year plus
- Location –Remote ( Hiring office Hyderabad, Bengaluru, Noida)
- Salary –upto 45 K PM
MICROSOFT CAREERS, WORK FROM HOME – DATA SCIENTIST INTERNSHIP RESPONSIBILITIES
- Data Collection and Preparation: Assisting in the collection, cleaning, and preprocessing of data from various sources to ensure its accuracy and suitability for analysis.
- Data Analysis: Conducting exploratory data analysis to gain insights into the data, identify patterns, and discover meaningful trends.
- Model Development: Assisting in the development of predictive models, machine learning algorithms, and statistical models to solve specific business problems.
- Model Evaluation: Evaluating the performance of developed models using appropriate metrics and conducting model testing to ensure their effectiveness.
- Data Visualization: Creating visualizations and dashboards to effectively communicate data insights to stakeholders and decision-makers.
- Research and Literature Review: Assisting in research activities to stay updated with the latest developments and advancements in the field of data science.
MICROSOFT CAREERS, WORK FROM HOME – SKILLS REQUIRED
- Programming Languages: Proficiency in programming languages commonly used in data science, such as Python, R, or SQL, is essential for data manipulation, analysis, and modeling.
- Data Manipulation: Ability to clean, preprocess, and transform data using various techniques to ensure its quality and readiness for analysis.
- Statistics and Mathematics: A strong foundation in statistical concepts and mathematical principles is crucial for developing and evaluating data models.
- Machine Learning: Familiarity with machine learning algorithms and techniques for classification, regression, clustering, and recommendation systems will be beneficial for building predictive models.
How To Apply?
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