Data Science tranier
2 days ago
Data Manipulation: Proficiency in working with data using tools like SQL, Python, or R to extract, transform, and load data from various sources. This includes skills in data cleaning, data wrangling, and data integration.
Statistical Analysis: Understanding of statistical concepts and techniques such as hypothesis testing, regression analysis, correlation, and sampling methods. This enables data analysts to draw meaningful conclusions and identify patterns or relationships in data.
Data Visualization: Ability to create clear and effective visual representations of data using tools like Tableau, Power BI, or Python libraries like Matplotlib or Seaborn. Data analysts should be able to create charts, graphs, and dashboards that effectively communicate insights to non-technical stakeholders.
Problem-Solving: Strong analytical and critical thinking skills to approach complex business problems, define analytical frameworks, and develop solutions based on data-driven insights. This includes the ability to identify relevant data sources and apply appropriate analysis techniques.
Data Mining and Data Exploration: Familiarity with techniques for exploring and discovering patterns or trends in data. This involves skills in data querying, data profiling, and data mining to uncover insights and identify areas of opportunity.
Data Tools and Technologies: Proficiency in using data analysis tools and technologies such as Excel, SQL, Python, R, and data visualization tools. Familiarity with databases and data querying languages is also important.
Job Type: Full-time
Pay: ₹10, ₹20,000.00 per month
Education:
- Bachelor's (Preferred)
Work Location: In person
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