
Data Analyst
1 week ago
Role Overview:
We are looking for a Data Analyst with strong Python expertise to join our growing Analytics Team in Kolkata. The ideal candidate will have 3-4 years of experience in data analysis using Python, with hands-on skills in data manipulation, statistical logic, and backend data workflows. This is a full-time, on-site position requiring daily collaboration with cross-functional teams to deliver insights and scalable data solutions.
Key Responsibilities:
1. Use Python to clean, transform, and analyze structured and semi-structured datasets.
2. Employ Pandas, NumPy, and related libraries to develop robust, reusable data workflows.
3. Extract and manipulate data efficiently using complex SQL queries from multiple relational databases.
4. Apply statistical methods and logic checks to validate assumptions and interpret results.
5. Collaborate with Data Scientists and Project Stakeholders to translate business requirements into data logic.
6. Write and maintain clean, well-documented Python scripts for repeatable analysis tasks and backend data processing.
7. Perform data validation, mapping, and reconciliation using Python and Advanced Excel.
8. Follow best practices in version control (e.g., Git) and maintain clear documentation for analytics processes.
9. Apply statistical techniques such as regression analysis (linear, logistic) and hypothesis testing to derive actionable insights from business data.
Required Skills & Qualifications:
1. Bachelors degree in Computer Science, Statistics, Mathematics, or a related technical field.
2. 34 years of experience in a data analyst or data operations role with Python as the primary tool.
3. Strong knowledge of Python libraries such as Pandas, NumPy, Openpyxl, etc.
4. Proficient in SQL with the ability to write optimized, multi-table queries.
5. Strong Excel skills for data verification and supplementary reporting.
6. Knowledge of data visualization tools like Tableau or Power BI is beneficial.
7. Experience working with Git repositories, agile environments, and code documentation.
8. Sharp analytical thinking and a strong sense of ownership toward deliverables.
9. Working knowledge of regression models (linear, logistic) and familiarity with libraries such as Statsmodels or scikit-learn for statistical analysis.
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