Data Science Manager

Key Responsibilities Manage team of Data Scientists and Data Science interns Teach, lead, and counsel colleagues on new techniques or solutions Collaborate with data and software engineers to enable deployment of sciences and technologies that will scale across the companys ecosystem Responsible for the conception, planning, and prioritizing of data projects Responsible for building analytic systems and predictive models as well as experimenting with new models and techniques Ensure that data projects align with organizational goals Minimum Qualification Master's degree in Computer Science, Data Science, Statistics or related technical field 5+ years of experience solving analytical problems using quantitative approaches Experience communicating quantitative analysis results Knowledge with relational databases and SQL Development experience in any scripting language (PHP, Python, Perl, etc.) Knowledge of statistics (e.g., hypothesis testing, regressions) Experience manipulating data sets through statistical software (ex. R, SAS) or other methods Technical Skills - Must have Programming Python (Preferred) / R ML Models i. Regression Linear, Logistic, Multinomial, Mixed effect Classification Bagging & Boosting, Decision tree, SVM Clustering K-Means, hierarchical, DB-Scan Time series ARIMA, SARIMA, ARIMAX, Holt-Winters, Multi TS (VAR), UCM Neural Networks (Deep learning), Naive Bayes Excel and SQL Dimensionality Reduction PCA, SVD etc. Optimization Techniques Linear programming, Gradient Descent, Genetic Algorithm Cloud Understanding of Azure / AWS offerings, Setting up ML pipeline of cloud Knowledge of Lending Business and Financial Services (Risk and Collection Analytics Key Responsibilities Manage team of Data Scientists and Data Science interns Teach, lead, and counsel colleagues on new techniques or solutions Collaborate with data and software engineers to enable deployment of sciences and technologies that will scale across the companys ecosystem Responsible for the conception, planning, and prioritizing of data projects Responsible for building analytic systems and predictive models as well as experimenting with new models and techniques Ensure that data projects align with organizational goals Minimum Qualification Master's degree in Computer Science, Data Science, Statistics or related technical field 5+ years of experience solving analytical problems using quantitative approaches Experience communicating quantitative analysis results Knowledge with relational databases and SQL Development experience in any scripting language (PHP, Python, Perl, etc.) Knowledge of statistics (e.g., hypothesis testing, regressions) Experience manipulating data sets through statistical software (ex. R, SAS) or other methods Technical Skills - Must have Programming Python (Preferred) / R ML Models i. Regression Linear, Logistic, Multinomial, Mixed effect Classification Bagging & Boosting, Decision tree, SVM Clustering K-Means, hierarchical, DB-Scan Time series ARIMA, SARIMA, ARIMAX, Holt-Winters, Multi TS (VAR), UCM Neural Networks (Deep learning), Naive Bayes Excel and SQL Dimensionality Reduction PCA, SVD etc. Optimization Techniques Linear programming, Gradient Descent, Genetic Algorithm Cloud Understanding of Azure / AWS offerings, Setting up ML pipeline of cloud Knowledge of Lending Business and Financial Services (Risk and Collection Analytics