We are looking for a detail-oriented Python Data Analyst to collect, clean, analyze, and interpret large datasets to support business decisions. The ideal candidate must have strong skills in Python, data visualization, SQL, and the ability to convert raw data into clear insights.
Key Responsibilities
Collect, clean, and preprocess structured & unstructured data.
Perform data analysis, trend identification, and exploratory data analysis (EDA).
Build scripts, automation, and dashboards using Python.
Create and maintain data visualizations using tools like Matplotlib, Seaborn, Plotly, or Power BI/Tableau.
Query large datasets using SQL and optimise data retrieval.
Work closely with business, product, and engineering teams to interpret data findings.
Prepare reports, summaries, and presentations for stakeholders.
Develop predictive insights through statistical models (basic ML preferred).
Ensure data accuracy, integrity, and secure handling of sensitive information.
Required Skills
Strong hands-on experience in Python for data cleaning & analysis.
Expertise in Python libraries: Pandas, NumPy, Matplotlib, Seaborn.
Solid understanding of data analysis, EDA, statistics, and business metrics.
Proficiency in SQL (MySQL, PostgreSQL, or any RDBMS).
Experience with Excel (VLOOKUP, pivot tables, formulas).
Ability to work with large datasets and optimise performance.
Good analytical thinking, problem-solving and communication skills.
Preferred skills
Knowledge of machine learning basics (scikit-learn).
Experience with data visualization tools - Power BI, Tableau.
Familiarity with ETL pipelines, APIs, or automation.
Understanding of cloud platforms (AWS/GCP/Azure).
Experience working with NoSQL databases (MongoDB).
Education Qualification
Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or related field.
Certifications in Python, Data Analytics, or SQL are a plus.
Job Types: Full-time, Contractual / Temporary
Pay: ₹341.53 - ?2,000.00 per hour
Benefits:
Work from home
Work Location: Remote
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