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Data Analyst

No of Positions  No of Positions:   1

location Location: Thiruvananthapuram

date Tentative Start Date:   July 10, 2023

Work From Work From : Offsite

rate Rate : $ 10  -  12 (Hourly)

experience Experience : 3 to 4 Year

Job Applicants : 9
Job Views : 712
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Job Category : Information Technology & Services
Duration : 3-6  Month
Key Skills Required Skills
Data Analyst Power BI SQL Python
Description

A data analyst is responsible for collecting, organizing, and analyzing large sets of data to provide insights and support decision-making processes within an organization. They use
various tools and techniques to extract valuable information from data and present it in a clear and understandable manner. Here is a detailed job description for a data analyst role:
1. Data Manipulation: Collect, clean, and transform data from various sources to ensure its accuracy and usability. Use SQL, Excel, Python, or other programming languages to manipulate and preprocess data as needed.
2. BI/Report Development: Develop and maintain business intelligence (BI) reports and dashboards that provide meaningful insights and visualizations to stakeholders. Use tools like
Tableau, Power BI, or Excel to create reports and visualizations that help in understanding key performance indicators (KPIs) and trends.
3. Data Modeling: Design and implement data models to organize and structure data for efficient analysis. Use tools like Excel, SQL, or data modeling software to create logical and physical data models that support data analysis and reporting requirements.
4. Data Analysis: Apply statistical techniques and data mining methods to extract insights and identify patterns in data. Perform exploratory data analysis, conduct hypothesis testing, and build predictive models to support business decision-making.
5. Data Visualization: Present data analysis results in a visually appealing and easy-to-understand manner. Use charts, graphs, and other visualizations to communicate key findings and trends effectively.
6. Data Quality Assurance: Ensure data accuracy, completeness, and integrity by conducting regular data quality checks. Identify and resolve data quality issues, such as missing or
inconsistent data, and collaborate with stakeholders to improve data collection and maintenance processes.
7. Collaborative Problem Solving: Work closely with cross-functional teams, such as business stakeholders, data engineers, and data scientists, to define analytical requirements and provide insights that drive business outcomes. Collaborate on data-related projects and contribute to data-driven decision-making processes.
8. Continuous Learning: Stay updated with the latest tools, technologies, and industry trends in data analysis and data management. Continuously improve data analysis skills and expand knowledge of statistical analysis, machine learning, and data visualization techniques.

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