Data Analyst
Budget: ₹100 – ₹400 INR
We are looking for a full time resource for a UK based firm with excellenet command in English for longer period.
The candidate should have following skills:
1. Data Cleaning & Preparation
• Removing duplicates: Use Remove Duplicates to eliminate redundant data.
• Data Validation: Ensure data accuracy by setting validation rules (e.g., dropdowns, specific formats).
• Text Functions: TRIM, LEFT, RIGHT, MID, FIND, and CLEAN for cleaning and parsing text data.
2. Data Manipulation & Transformation
• Sorting & Filtering: Sort data based on specific criteria and use Filter to isolate key data points.
• Lookup Functions: VLOOKUP, HLOOKUP, INDEX, MATCH for finding data within a dataset.
• Logical Functions: IF, AND, OR, IFERROR to handle conditional logic and errors.
3. Data Analysis
• Pivot Tables: Summarize, group, and analyse large datasets efficiently.
• Data Summarization Functions: SUM, AVERAGE, COUNT, COUNTA, SUMIFS, COUNTIFS, AVERAGEIFS.
• Statistical Functions: STDEV, VAR, CORREL, PERCENTILE for basic statistical analysis.
4. Data Visualization
• Charts & Graphs: Create bar charts, line graphs, pie charts, scatter plots, and histograms.
• Conditional Formatting: Highlight key data patterns using colour codes and custom formatting rules.
5. Advanced Excel Functions
• Array Formulas: Use INDEX-MATCH, SUMPRODUCT, and dynamic arrays for complex calculations.
• Power Query: Import, transform, and load data from different sources for analysis.
• Data Tables: Use What-If Analysis and create data tables to evaluate different scenarios.
6. Basic Automation
• Macros: Record and write simple macros to automate repetitive tasks in Excel.
7. Error Handling & Auditing
• Formula Auditing: Trace precedents and dependents of formulas to ensure accuracy.
• Error Checking: Use IFERROR, ERROR.TYPE to handle and debug errors effectively.
The candidate should have following skills:
1. Data Cleaning & Preparation
• Removing duplicates: Use Remove Duplicates to eliminate redundant data.
• Data Validation: Ensure data accuracy by setting validation rules (e.g., dropdowns, specific formats).
• Text Functions: TRIM, LEFT, RIGHT, MID, FIND, and CLEAN for cleaning and parsing text data.
2. Data Manipulation & Transformation
• Sorting & Filtering: Sort data based on specific criteria and use Filter to isolate key data points.
• Lookup Functions: VLOOKUP, HLOOKUP, INDEX, MATCH for finding data within a dataset.
• Logical Functions: IF, AND, OR, IFERROR to handle conditional logic and errors.
3. Data Analysis
• Pivot Tables: Summarize, group, and analyse large datasets efficiently.
• Data Summarization Functions: SUM, AVERAGE, COUNT, COUNTA, SUMIFS, COUNTIFS, AVERAGEIFS.
• Statistical Functions: STDEV, VAR, CORREL, PERCENTILE for basic statistical analysis.
4. Data Visualization
• Charts & Graphs: Create bar charts, line graphs, pie charts, scatter plots, and histograms.
• Conditional Formatting: Highlight key data patterns using colour codes and custom formatting rules.
5. Advanced Excel Functions
• Array Formulas: Use INDEX-MATCH, SUMPRODUCT, and dynamic arrays for complex calculations.
• Power Query: Import, transform, and load data from different sources for analysis.
• Data Tables: Use What-If Analysis and create data tables to evaluate different scenarios.
6. Basic Automation
• Macros: Record and write simple macros to automate repetitive tasks in Excel.
7. Error Handling & Auditing
• Formula Auditing: Trace precedents and dependents of formulas to ensure accuracy.
• Error Checking: Use IFERROR, ERROR.TYPE to handle and debug errors effectively.