PRITESHKUMAR RANA

Detail-focused Data Analyst with robust experience in data warehousing, validation processes, and business needs analysis. Proficient in assessing large datasets to determine impactful trends, translating them into actionable insights. Demonstrates a high level of organization, attention to detail, and a passion for Big Data and Data Analytics.

• Python Developer - Tops Technologies (April 2021)
• Data Science Job Simulation - British Airways (June 2024)
• Power BI Job Simulation - PwC Switzerland (June 2024)
• Data Science Job Simulation - BCG X (June 2024)
• BCG X Data Science Job Simulation – BCG X Boston (June 2024)
• Data Analytics and Visualization Job Simulation – Accenture North America (June 2024)
• Artificial Intelligence Job Simulation – Cognizant USA (June 2024)
• Data Visualisation: Empowering Business with Effective Insights – TATA India (June 2024)
• Data Analytics Job Simulation – Quantium Australia (June 2024)
• Advanced Software Engineering Job Simulation - Walmart USA (Jun 2024)

• Led a project which led to an increase in customer satisfaction rates by 10%.
• Was awarded for being the best customer service performer.
• Reduced handling times and increased process efficiency by 20%.
• Ranked 1st in the whole country in a coding challenge - demonstrated exceptional ability to.

• Active participant in local Data Science meetups and conferences.
• Volunteer at Toronto Data Science Community.
• Contributor to open-source projects on GitHub, focusing on data analysis and machine learning.
• Engaged in online forums and discussion groups related to data analytics and Python programming.

• Proficient in data analysis tools and software (e.g., SQL, Python, R)
• Excellent communication and teamwork abilities
• Experience in visualization techniques and business intelligence platforms
• Strong analytical and problem-solving skills
• Knowledge in statistical methods and predictive modeling

Emotion Recognition Using Facial Detection

Tools & Technologies: Python, Django, HTML, CSS, JavaScript

• Developed an application integrating emotion detection with facial recognition to suggest music based on mood.
• Utilized a facial images dataset to train a model, recognizing facial emotions and categorizing them into moods like happy or sad.
• Integrated with Spotify to play music corresponding to the detected mood.
• Implemented a drowsiness detection feature to alert drivers, enhancing safety.
• Deployed the system on a live web server allowing users to sign up and utilize the service for mood enhancement and safety features.

Medical Billing Data Analysis

Tools & Technologies: Python, Pandas, NumPy, Scikit-learn, Keras, and Tableau

• Conducted an in-depth exploration and automation of diagnosis coding via machine learning.
• Built a predictive machine learning model to identify medical procedure codes from clinical narratives, reducing human error and improving operational efficiency.
• Utilized datasets including clinical keywords and narratives to train and test the model.
• Implemented data preprocessing techniques, including text normalization and TF-IDF vectorization.
• Achieved a model training accuracy of 99%, demonstrating the effectiveness of the solution in managing complex medical coding requirements.