This job opportunity at Bhavi Artificial Intelligence Technologies seems like a great entry point for someone interested in applying data science and machine learning techniques to real-world problems, particularly in the realm of finance and time series analysis. Here's a summary of what the position entails:
- Position: Data Scientist
- Company: Bhavi Artificial Intelligence Technologies
- Location: Hyderabad
- Experience: 0-2 years
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Responsibilities:
- Stock Market Data Analysis: Utilizing rule-based algorithms and various machine learning techniques for analyzing stock market datasets, including time series forecasting using Python and deep learning.
- Machine Learning Data Processing Pipelines: Designing and building scalable data processing pipelines for efficient handling of financial data, including data cleaning, transformation, and feature engineering.
- Real-time Flask-based APIs: Developing robust and secure Flask-based APIs for real-time access to ML models and analysis results, ensuring efficient handling of multiple concurrent requests.
- Python and Django Web Interfaces: Building user-friendly web interfaces using Python and Django to interact with APIs and visualize analysis results, creating intuitive and responsive front-end designs.
- Database Management: Setting up and maintaining secure databases for financial datasets and model outputs, optimizing database performance, and ensuring data integrity.
- Cloud Deployment: Deploying ML data processing pipelines and web applications on scalable cloud solutions, implementing best practices for reliable and cost-effective cloud deployment.
Required Skills:
- Amazon Web Services (AWS)
- Data Analytics
- Data Science
- Machine Learning
- Natural Language Processing (NLP)
- Python
- SQL
Additional Requirements:
- Willingness to work in the Hyderabad office.
- Able to start the work-from-home job within the next week.
- Availability for a minimum duration of 6 months.
- Relevant skills and interests.
Salary: ₹2,40,000 - ₹3,60,000 per year
APPLY NOW: CLICK HERE
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