Data Analyst
Zetheta Algorithms Private Limited India
Job Description
"Unlock the secrets of Zetheta Algorithms Private Limited as a Data Analyst, shaping the future of FinTech with innovative AI tools."
Embark on an extraordinary journey as a Data Analyst intern at Zetheta Algorithms Private Limited, a FinTech start-up that's revolutionizing the space with cutting-edge AI tools.
As a self-driven, analytically-minded student with a passion for extracting meaningful insights from complex datasets, you'll contribute to data-driven decision making and work on cutting-edge projects involving data collection, processing, analysis, and visualization in financial markets.
Why you should learn this:
High demand for Data Analysts in the FinTech industry, with a projected growth rate of 14.1% in the next 5 years.
Expected Salary: ₹25,000 - ₹50,000 per month, depending on experience and qualifications.
How it works:
- Step 1: Collect and process large datasets from financial markets using Python libraries like Pandas and NumPy.
- Step 2: Apply data analysis and visualization techniques to extract meaningful insights and present findings to stakeholders.
Core Concepts to Master
Data Wrangling
A deep dive into data cleaning, preprocessing, and transformation techniques using Python libraries like Pandas and NumPy.
Data Visualization
A comprehensive overview of data visualization techniques using libraries like Matplotlib, Seaborn, and Plotly to effectively communicate insights to stakeholders.
Machine Learning
A detailed exploration of machine learning concepts, including supervised and unsupervised learning, regression, classification, and clustering using Python libraries like Scikit-learn and TensorFlow.
Interview Questions (Beginner)
- What is data wrangling, and why is it important in data analysis?
- What are some common data visualization techniques used in data analysis?
- Can you explain the difference between supervised and unsupervised learning?
Job Overview
Advance Questions
- • How would you approach data analysis for a large dataset with missing values?
- • Can you describe a scenario where you would use clustering algorithms in data analysis?
- • How would you evaluate the performance of a machine learning model?