Experienced and proficient in implementing statistical solutions and machine learning solutions across various business problems. Good at converting business/client requirements into analytical solutions. Built models across different domains like Banking, Financial, Health care, pharmaceutical, retail, insurance, location-based services, etc.
RESPONSIBILITIES:
● Data Scientist with 6 years of experience in building various models with end to end operations like Business understanding, problem identification, data collection, data understanding, data cleaning, and model building.
● Implemented various techniques to improve the model accuracy like ○ Different Feature selection techniques, Feature Scaling, Different Feature transformation techniques, etc.
● Worked in multiple parts for Retail, Banking, Health care, Insurance, etc.
● Experienced in validating the model based on stability, accuracy, transparency, etc.
●Experienced in performing various data operations like missing value treatment, outlier treatment, text-based, special characters, huge size databases, etc.
● Worked with different teams to understand the business and to implement successful solutions.
●Implemented brainstorming sessions, interviews, and expert meetings to identify the client demand and key challenges.
ANALYTICAL SKILLS:
Optimization techniques, Confusion matrix, Reliability models, Stochastic models, Bayesian models, Classification model, Cluster analysis, Anomaly detection, non-parametric methods, Recursive Feature Elimination, PCA, Word cloud, Semantic Networks, Neural Networks, machine learning, deep learning, computer vision, natural language processing, data science e.t.c.
TOOLS:
✓ Python ✓ R-programming ✓ SAS ✓ PySpark ✓ Caffe ✓ Tensorflow ✓ Keras ✓ Sckit-Learn ✓ Tableau Desktop & Server ✓ R Shiny ✓ SQL ✓ Git ✓ Docker ✓ Jenkin