SUMMARY

• Data Science Certification both in Python and Rd from Simplilearn
• Machine Learning Advanced Certification wif Python and Deep Learning wif TensorFlow from Simplilearn
• R Programming A - Z™, Advanced Analytics, Data Science and ML Bootcamp wif R from Udemy
• Business Analytics wif Excel, Statistics Essentials for Data Science from Simplilearn
• Certification on Apache Spark wif Python, Certification in Tableau 10
• Strong problem solving and analytical skills and domain expertise in insurance, economics and epidemiology
• Proficient in python libraries (Pandas, NumPy, SciPy, Scikit-learn), Jupyter, web scraping and Spark MLlib
• Expertise in both R and Python to manipulate data and draw insights from large data sets using cloud
• Experienced wif data wrangling, data cleaning and dimensionality reduction and predictive modelling skills
• Excellent in machine learning techniques (regression, decision tree, random forest, artificial neural) networks, etc.) and their real-world advantages/drawbacks
• Expertise in both Supervised (Regression/LASSO, SVM, Neural Networks) and Unsupervised (Association, Clustering) Machine Learning algorithms
• Proficient in Deep Learning techniques (RNNs/CNNs/LSTMs/GANs) and their applicability using TensorFlow on Cloud (AWS, google) based analytics platforms
• Command in Natural Language Processing, tokenization, parsing, stemming, TF-IDF)
• Excellent reporting or visualization using Tableau or Power BI
• Competent in model validation, optimization, hyperparameter tuning and regularization (Ridge/LASSO)
• Working knowledge on GitHub, RDMS, SQL
• Experienced in time series: forecasting wif AR, MA, ARMA, ARIMA and Winter model

PROFESSIONAL EXPERIENCE

Data Scientist/Data Analyst

Confidential, Sacramento CA

Responsibilities:

• Prepared dashboard using Tableau for marketing KPI, imported various files and merged them together
• Accomplished predictive modeling on different customers’ segmentation and propensity score matching data
• Classified clients profile using KNN algorithms using Python
• Used regression analysis to predict utility consumption by different client using python
• Updated live data, cleaned and standardized them for integration purposes
• Manipulated large PRIZM and Clarity data in excel

Data Scientist/Data Analyst

Confidential, Sacramento, CA

Responsibilities:

• Carried out data analysis on sales and inventory requirements by using python in AWS
• Accomplished machine learning algorithms in teh AWS cloud using python to predict and optimize revenue
• Refined dashboard, visualized sales using Tableau and demand of profitable goods
• Achieved high quality customer services feedback to meet company standard
• Compared exploratory data analysis in python for women wif and wifout insurance
• Accomplished logistic model in teh AWS cloud using python library to predict reduction in maternal mortality
• Used logistic regression ML algorithm using Python libraries to predict reduction in maternal mortality
• Carried out regression and predicted 10 percent increase in women enrollment over a 4-month period

Data Analyst/Consultant

Confidential

Responsibilities:

• Contributed to literature reviews on casualty insurance
• Extracted data, cleaned, modelled and visualized them using Tableau, excel and SQL
• Carried out Exploratory Data analysis (outliers detection, modeling and imputation) using python
• Cleaned, explore and visualized casualty insurance data using Python
• Predicted insurance claim size, number using machine learning algorithms viz regression model
• Optimized teh logit model, decision tree and random forest to predict fraud claim in insurance
• Recommended best classification model wif tested accuracy and validation

Data Analyst/Consultant

Confidential

Responsibilities:

• Reviewed social insurance models in Thailand, South Korea, India, Tunisia and Turkey
• Imported data, performed exploratory data analysis using R
• Extracted, load, model,and reconcile data across different segmentations and compared their visualization
• Experienced in pattern recognition, feature engineering//extraction and data visualization using Tableau
• Applied machine learning algorithms such as regression to model and predicted future revenue and claim
• Tested model validation, accuracy and hyperparameter tuning for teh best model
• Achieved in business process reengineering, modelling, systems development and analytical skills
• Delivered power point Presentations, disseminated highlights and assimilated stakeholders’ queries
• Accomplished, independently, a policy report on social insurance for teh government of Nepal
• Achieved government approval and implemented after 5 year back
• Taught US life & health insurance, retirement benefits, Managed care, HMO, PPOs to undergraduate students
• Familiarized wif advanced statistical, econometrics techniques and concepts (regression, properties of distributions, statistical tests etc.) and experience wif their applications
• Explained part of machine learning algorithms like linear and logistic regression to model claim and fraud
• Delivered class on statistical distribution, probability and hypothesis testing
• Carried out class on linear algebra, matrix and optimization using advance calculus
• Taught domestic and international multi-payer vs universal insurance mechanism
• Possessed visualization, presentation communication skills among stakeholders

Actuarial/Data Analyst

Confidential

Responsibilities:

• Analyzed sales data on different life products, trend and their prediction using regression
• Provided advanced analytical support for sales, training and report for more TEMPthan 500 sales team
• Extracted premium, sum assured and claim data using SQL and their visualization
• Analyzed and reconciled large data set in excel and communicated to clients for update
• Forecast future life expectancy and estimated interest rate using long-term bond rate
• Generated gratuity and leave-encashment valuation, furnished reports as per AS15, FASS 88 and GAAP