Umesh Karki
Halifax,Nova Scotia
Summary
A Data Scientist with almost 1.5 years of experience executing data-driven solutions to increase efficiency, accuracy, and utility of internal data processing. Experienced at creating data regression models, using predictive data modelling, and analyzing data mining algorithms to deliver insights and implement action-oriented solutions to complex business problems. Data Scientist familiar with gathering, cleaning and organizing data for use by technical and non-technical personnel. Advanced understanding of statistical, algebraic and other analytical techniques. Highly organized, motivated and diligent with significant background in [Area of expertise].
Overview
2
2
years of professional experience
2
2
years of post-secondary education
Work History
Associate Data Scientist
Everest Drain and Plumbing
Toronto, ON
03.2021 - Current
- Involved in Classification technique like Multinomial Logistics Regression in to find the
- Model/Manufacturer and the equipment Defect status, achieving 30 % more accurate prediction of performance than previous years
- Performed Sentiment Analysis of Work Order Notes by using Multinomial Naive Bayes highlighting safety related keywords, thereby taking precautionary steps to avoid workplace injury
- Performed Exploratory Data Analysis, Class Imbalance and Dimensionality Reduction while performing the Machine learning algorithm -
- PROJECTS
- Rene Wind
- Course Model Tuning "Rene Wind" is a company working on improving the machinery/processes involved in the production of wind energy using machine learning and has collected data of generator failure of wind turbines using sensors
- The objective is to build various classification models, tune them and find the best one that will help identify failures so that the generator could be repaired before failing/breaking and the overall maintenance cost of the generators can be brought down.
Education
Post Graduate - Data Science and Business Analytics
The University of Texas at Austin McCombs School of Business
Bachelor - Business
Tribhuvan University
Advance Diploma - Accounting
Australian Collage of Management and Technology
Diploma in Marketing - Marketing
Lamart Collage of Technology
Sydney Australia 11.2008 - 11.2010
Skills
Machine LearningClassification, Regression, Clustering, Decision Trees, K-Means ClusteringStatistical Methods: Predictive Analysis, Hypothesis Testing and Confidence Intervals, Principal, NumPy, Panda, Matplotlib, Seaborn, pyplot, sklearnComponent Analysis and Dimensionality Reduction, Market Basket Analysis, Text AnalyticsProgramming Languages: R, Python I Big Data Language: HadoopScripting Language: Database Language: SQLData Extraction Tool: Informatica Data Reporting Tool: TableauSkills and ToolsUp and down sampling, Regularization, Hyperparameter tuningEasy VisaCourse Ensemble TechniquesAnalyse the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or deniedEDA, Data Pre-processing, Customer Profiling, Bagging Classifiers (Bagging and Random Forest), Boosting Classifier (AdaBoost, Gradient Boosting, XG Boost), Stacking Classifier, Hyperparameter Tuning using Grid Search CV, Business insightsINN HotelsCourse Supervised Learning - ClassificationAnalyse the data of INN Hotels to find which factors have a high influence on booking cancellations, build a predictive model that can predict which booking is going to be cancelled in advance, and help in formulating profitable policies for cancellations and refundsEDA, Data Pre-processing, Logistic regression, Multicollinearity, Finding optimal threshold using AUC-ROC curve, Decision trees, PruningRe-CallCourse Supervised Learning - FoundationsAnalyse the used devices dataset, build a model which will help develop a dynamic pricing strategy for used and refurbished devices, and identify factors that significantly influence the priceEDA, Linear Regression, Linear Regression assumptions, Business insights and recommendationsE-news Express ProjectCourse Business StatisticsThis project used statistical analysis, a/b testing, and visualization to decide whether the new landing page of an online news portal (E-news Express) is effective enough to gather new subscribers or not The simulated dataset has certain important metrics such as converted status and time spent on the page that will help to conclude the effectiveness of the new landing page Apart from that, the dependence of conversion on the preferred language will also be analysed in this projectHypothesis Testing, a/b testing, Data Visualization, Statistical InferenceFood Hub Order Analysis using PythonVisible to publicCourse Python - FoundationsThe food aggregator company has stored the data of the different orders made by the registered customers in their online portal They want to analyze the data to draw some actionable insights for the business Suppose you are hired as a Data Scientist in this company and the Data Science team has shared some of the key questions that need to be answered Perform the data analysis to find answers to these questions that will help the company to improve the businessExploratory Data Analysis (Variable Identification, Univariate analysis, Bi-Variate analysis), PythonData Visualization tool :- Tableau, Microsoft Power BI ,Excel and Quick View
Timeline
Associate Data Scientist
Everest Drain and Plumbing
03.2021 - Current
Diploma in Marketing - Marketing
Lamart Collage of Technology
11.2008 - 11.2010
Post Graduate - Data Science and Business Analytics
The University of Texas at Austin McCombs School of Business
Bachelor - Business
Tribhuvan University
Advance Diploma - Accounting
Australian Collage of Management and Technology