Data Anaytics Internship In Bangalore at GE Appliances (REQ-20933)

October 2, 2024

Description:

Internship Opportunity: Python Scripting and Machine Learning

As an intern, you will engage in Python scripting to automate data processes, develop machine learning models, and create user interfaces for accessing SQL databases.

Key responsibilities:

Understand Data Automation Requirements: Rapidly grasp and evaluate data automation needs to align with project objectives.
Develop and Maintain Automation Scripts: Write and uphold Python scripts to automate tasks related to data collection, cleaning, and processing, ensuring high efficiency and accuracy.
Convert R Scripts to Python: Review existing automation scripts in R and transition them to Python, focusing on optimizing performance and maintainability.
Leverage AI and NLP Technologies: Utilize Large Language Models (LLMs), OpenAI (Generative AI) API, and advanced Natural Language Processing (NLP) techniques to enhance data relevance and insights. Create a user interface for seamless database information retrieval.

Qualifications requirements:

Final year B.Tech or completed B.Tech in Computer Science Engineering.

Technical skills:

Python Programming: Advanced skills in Python, with experience in libraries such as Pandas, NumPy, Scikit-learn, NLTK, SpaCy, OpenAI, and Sentence-transformers. Proficient in implementing machine learning algorithms like Gradient Boosting, ADASYN, and cosine similarity.
Large Language Models (LLMs): Experience in utilizing and evaluating models such as BERT for advanced NLP tasks, understanding their strengths and limitations.
Natural Language Processing (NLP): Expertise in advanced NLP techniques and their integration into Python scripts for in-depth data analysis.
Full-Stack Development: Knowledge of front-end (HTML, CSS, JavaScript) and back-end (Python, Flask, Django) technologies for developing interactive applications.
R Programming: Strong proficiency in R for statistical analysis and data visualization.
SQL Databases: Solid understanding of relational databases and SQL for effective data storage and retrieval.
NoSQL Databases: Familiarity with NoSQL databases like MongoDB for managing unstructured data.
Jupyter Notebooks: Proficient in using Jupyter Notebooks for interactive data analysis and visualization.
Integrated Development Environments (IDEs): Experience with IDEs such as PyCharm and VS Code for efficient coding and debugging.
Prompt Engineering: Skilled in designing and optimizing prompts for diverse NLP applications.
Version Control: Basic knowledge of version control systems like Git for effective project collaboration.
Data Security: Understanding of data security practices and compliance policies for secure data management.
OpenAI API: Experience with the OpenAI API and its applications for advanced AI and NLP tasks.
MS Office Suite: Proficient in MS Office Suite, especially Excel, for data manipulation and reporting.
Passion for Data Science: Strong interest in data science and a commitment to continuous learning and professional growth.