Natobotics
Data Analyst
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Analyst position based in London, offering a hybrid contract. It requires 6+ years of experience in Banking/Financial Services, strong SQL skills, proficiency in data visualization tools, and knowledge of Python/R.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
April 7, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
London, England, United Kingdom
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🧠 - Skills detailed
#Computer Science #"ETL (Extract #Transform #Load)" #Microsoft Power BI #Pivot Tables #BI (Business Intelligence) #Visualization #Data Extraction #Data Analysis #Python #SQL (Structured Query Language) #Tableau #R #VBA (Visual Basic for Applications) #Datasets #Statistics
Role description
Job Title: Data Analyst
Location: London
Job Type: Contract-Hybrid
Job Description
• Bachelor’s/Master’s degree in Computer Science, Statistics, Finance, or related field.
• 6+ years of experience as a Data Analyst in Banking / Financial Services.
• Strong proficiency in SQL for data extraction and manipulation.
• Experience with data visualization tools (Tableau, Power BI, or similar).
• Proficiency in Excel (advanced functions, pivot tables, VBA is a plus).
• Knowledge of Python / R for data analysis is preferred.
• Strong understanding of banking datasets (transactions, loans, customer data, risk data).
Job Title: Data Analyst
Location: London
Job Type: Contract-Hybrid
Job Description
• Bachelor’s/Master’s degree in Computer Science, Statistics, Finance, or related field.
• 6+ years of experience as a Data Analyst in Banking / Financial Services.
• Strong proficiency in SQL for data extraction and manipulation.
• Experience with data visualization tools (Tableau, Power BI, or similar).
• Proficiency in Excel (advanced functions, pivot tables, VBA is a plus).
• Knowledge of Python / R for data analysis is preferred.
• Strong understanding of banking datasets (transactions, loans, customer data, risk data).
