Mrutyunjaya Sahoo

• Identified, analyzed, and interpreted trends or patterns in complex data sets by finding correlations and visualizing with charts.
• Utilized various professional statistical techniques and maintained large databases to collect and analyze data from partners and customers.
• Completed data cleaning and data validation of existing spreadsheets to promote robust data management platform, resulting in accurate data analysis and entry.
• Interacted with clients for technical requests to understand business requirements in different project lifecycle phases.
• Created data models to support decision-making processes.
• Created dashboards to monitor and track key performance indicators.

• Participated in a team project on Abstractive Text Summarization using neural networks and natural language processing techniques
• Successfully achieved the required accuracy on a dataset of the articles
• Utilized
• TensorFlow and Python for implementation
• PROJECTS, Company Bankruptcy Prediction
• As part of my academic/professional experience, I successfully completed a Classification project on predicting bankruptcy in firms using large datasets obtained from the Taiwan Economic Journal spanning from 1999 to

• Certified Data Scientist from Almabetter Pvt Ltd, demonstrating proficiency in statistical analysis, machine learning algorithms, data visualization, and other data science techniques. Completed rigorous coursework and hands-on projects that showcased the ability to solve real-world business problems using data-driven insights
• Created data visualization graphics, translating complex data sets into comprehensive visual representations.
• Successfully completed a real-time company project involving the identification, analysis, and interpretation of trends in complex data sets using a range of supervised and unsupervised learning techniques. Demonstrated proficiency in data preprocessing, model selection, and hyperparameter tuning to achieve accurate and meaningful insights that informed business decisions.

PROJECTS:

Retail_Sales_Prediction:

• Developed a retail sales prediction model using machine learning algorithms to optimize inventory management and increase sales revenue.
• Implemented data preprocessing techniques and utilized regression analysis to forecast sales trends, resulting in a 10% increase in sales for the retail company.

CompanyBankruptcyPrediction :

• Built a machine learning model to predict the likelihood of a company going bankrupt, using financial data and feature engineering techniques. Achieved an accuracy rate of 85% in predicting bankruptcy, assisting clients in making informed investment decisions.
• Conducted extensive data analysis and feature selection to build a decision tree model that accurately predicted bankruptcies of various companies. Provided valuable insights to stakeholders in the finance industry, resulting in improved risk assessment and mitigation strategies.

OnlineRetailCustomerSegmentation :

• Conducted customer segmentation analysis using unsupervised machine learning techniques, such as K-means clustering and Principal Component Analysis (PCA), to identify distinct customer groups based on purchase behavior and demographics. Results led to tailored marketing strategies and a 20% increase in customer retention for the online retail company.
• Leveraged customer transaction data to develop a customer segmentation model, utilizing machine learning algorithms to identify and group customers based on purchase behavior and preferences. Generated actionable insights for the online retail business, such as personalized product recommendations and targeted promotions, resulting in a 15% increase in sales revenue