Data Analysis and Freelancing | Exploring New Technologies

{

"name": "Sushreeta",

"occupation": "AI & ML Engineer",

"likes": ["Writing Story", "Cooking"],

}

Resume

About Me

Enthusiastic and skilled professional with 4 years of experience in data analysis, project management, and collaborative problem-solving. Seeking a challenging position as a Data Analyst to leverage expertise in driving business success through insightful data analysis and effective project management.

My Professional Experience

Work Experience

Platform Analyst, Accenture, Bangalore, India(MARCH 2018 — SEPTEMBER 2020)

Work closely with business stakeholders to understand their needs, objectives, and challenges.
Elicit, document, and analyze business requirements, processes, and workflows.
Strong analytical and problem-solving skills with a keen attention to detail.
Proficient in data analysis tools like SQL, Excel, and Tableau.

Content Reviewer, Tata Consultancy Services, Hyderabad, India(SEPTEMBER 2017 — FEBRUARY 2018)

Write articles, bulletins, sales letters, speeches, and other related informative, marketing and promotional material.
Proficient in content moderation tools and platforms.
Strong attention to detail with a keen eye for content accuracy and compliance.
Excellent communication skills for providing clear and constructive feedback.
Familiarity with industry regulations and standards related to online content.
Ability to work effectively in a fast-paced and dynamic environment

Intern, Central Tool Room and Training Centre, India

Worked on PLC Programming and field instrument commissioning.
Handled Installation and commissioning.
Worked on panel design, wiring, testing, and commissioning.

Data Analysis Intern, Collins Aerospace, Bangalore, India

Using langchain(document analysis and summarization, chatbots)
Using Databricks ml flow & mlops for developing the AI model
Conducted in-depth analyses of engine components using XGBoost
Analyse data and Cleaning using Pandas and NumPy

Freelancer(Content Reviewer,Content Analyst & Digital marketing)Bangalore, India(SEPTEMBER 2014 — DECEMBER 2016)

Strong project management and organizational skills for effective task prioritization and time management.
Proficient in Digital Marketing, and content writing.
Adaptability to work on diverse projects and learn new skills as required.

Intern, DRDO, India

Relayed results to team members and management via briefings and written material.
Analysed results from simulation or real data to identify root causes and trends.
Hands-on Experience on bit-accurate simulation models of digital modem modules.

3 different internships

My PROJECT (link)

Twitter Toxicity Analysis Project

Online Food Services Website

Detects Toxicity percentages based on the given data.
Expertise in Python, Pandas, Data Analysis and Visualization.
Gather a large dataset of tweets labelled as hate speech, offensive language, or non-offensive content
Testing with different advanced machine-learning models Decision Tree, K Nearest Neighbors, and SVM.
Generates CSV of the toxicity data

I developed a basic online food services website using Django.
Create CURD using MySQL
Deploy your Django application on a web server like Heroku
Implement security measures like HTTPS, CSRF protection, and input
validation to secure your website.
Write unit tests for your Django app to ensure its functionality.

Air-Pen (Python, Open-CV, Computer Vision)

ChatGPT: Conversational AI Chatbot (Python, web scrapping, Flask, ChatGPT)

Captures Webcam feed using Open-CV.
This basic implementation allows you to write on the screen by moving the pen in the air.
Tracks a color especially a pen-type tool, visible on the feed.
Used to write on the screen by moving a pen in the air

Enter your inquiry or question in the chatbot interface.
The chatbot will process the input using ChatGPT and provide a response based on the available airline data.
Users can inquire about Flight Information, Ticket Pricing, Airport Information and Travel Advisories (security notices and COVID-19 guidelines)

Master Thesis: Data Science & Cloud Computing in the Aviation Industry (Python, Random Forest, XGBoost)

To create and train models using the Random Forest and XGBoost algorithms for forecasting the remaining useful life (RUL) of engines in the test dataset, you would typically follow these steps

Data Preprocessing: Load the dataset containing information about engines, such as sensor readings, operational conditions, and RUL.
Feature Engineering: Extract relevant features from the dataset that are useful for predicting RUL.
Model Training: Define a function to create and train models using Random Forest and XGBoost algorithms.
Model Evaluation: Evaluate the performance of the trained models using the testing dataset. Metrics such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared can be used to assess the accuracy of the models in predicting RUL.
Model Deployment: Compare the performance of the Random Forest and XGBoost models to determine which one performs better for this specific dataset. You can deploy it to make predictions on new data.