Lead Data Scientist

Salary Range: $172,994.00/year - $201,000.00/year Duties: Perform data discovery and build predictive and prescriptive models using machine learning algorithms and statistical methods. Apply data mining, analysis, modeling, and simulation techniques using standard tools and statistical methods. Build and implement models and algorithms following MDLC/MLOps and internal development standards. Present complex results in a clear, accessible way for non-technical stakeholders. Contribute to the planning and conversion of on premise data and analytics systems conversion to the Cloud in conjunction with IT. Utilize analytical, statistical, and programming skills to collect, analyze, and interpret large data sets. Use statistical tools/platforms including SAS, Python, and R to develop data-driven solutions to difficult business challenges. Partner with business stakeholders to identify and develop innovative modeling solutions and implement necessary monitoring to deploy models in production. Use standardized processes for managing the lifecycle of models and use appropriate tools to monitor and analyze model performance and data accuracy. Provide data and analytics to assist with budget development. Translate business objectives to data science problems and vice versa. Education & Experience Requirements: Master's degree in Statistics, Mathematics, Computer Science, Electrical Engineering or related field (willing to accept foreign education equivalent) plus three (3) years of experience as a Data Scientist or related occupation, driving model development, cloud analytics, and data-driven insights to support business decisions and stakeholder engagement; or, alternatively, a Bachelor’s degree in Statistics, Mathematics, Computer Science, Electrical Engineering or related field (willing to accept foreign education equivalent) plus five (5) years of experience as a Data Scientist or related occupation, driving model development, cloud analytics, and data-driven insights to support business decisions and stakeholder engagement. Specific skills/other requirements - Experience must include (quantitative experience requirements not applicable to this section): developing predictive models, reports, and dashboards using BI tools; building and deploying statistical and machine learning solutions using linear/logistic regression, support vector machines, deep neural networks, and Random Forest; managing, retrieving, and manipulating data from databases; performing project management using JIRA or any other project management software; utilizing SQL, Python, and R to analyze data, automate processes, and build predictive models; using AWS to deploy applications, manage cloud infrastructure, and optimize data storage; and, processing large-scale data, running fast queries, and analyzing distributed datasets using Hadoop, Presto, and Athena. Hybrid role - 3 days per week in office. Up to 5% domestic travel required.

Duties: Perform data discovery and build predictive and prescriptive models using machine learning algorithms and statistical methods. Apply data mining, analysis, modeling, and simulation techniques using standard tools and statistical methods. Build and implement models and algorithms following MDLC/MLOps and internal development standards. Present complex results in a clear, accessible way for non-technical stakeholders. Contribute to the planning and conversion of on premise data and analytics systems conversion to the Cloud in conjunction with IT. Utilize analytical, statistical, and programming skills to collect, analyze, and interpret large data sets. Use statistical tools/platforms including SAS, Python, and R to develop data-driven solutions to difficult business challenges. Partner with business stakeholders to identify and develop innovative modeling solutions and implement necessary monitoring to deploy models in production. Use standardized processes for managing the lifecycle of models and use appropriate tools to monitor and analyze model performance and data accuracy. Provide data and analytics to assist with budget development. Translate business objectives to data science problems and vice versa. Education & Experience Requirements: Master's degree in Statistics, Mathematics, Computer Science, Electrical Engineering or related field (willing to accept foreign education equivalent) plus three (3) years of experience as a Data Scientist or related occupation, driving model development, cloud analytics, and data-driven insights to support business decisions and stakeholder engagement; or, alternatively, a Bachelor’s degree in Statistics, Mathematics, Computer Science, Electrical Engineering or related field (willing to accept foreign education equivalent) plus five (5) years of experience as a Data Scientist or related occupation, driving model development, cloud analytics, and data-driven insights to support business decisions and stakeholder engagement. Specific skills/other requirements - Experience must include (quantitative experience requirements not applicable to this section): developing predictive models, reports, and dashboards using BI tools; building and deploying statistical and machine learning solutions using linear/logistic regression, support vector machines, deep neural networks, and Random Forest; managing, retrieving, and manipulating data from databases; performing project management using JIRA or any other project management software; utilizing SQL, Python, and R to analyze data, automate processes, and build predictive models; using AWS to deploy applications, manage cloud infrastructure, and optimize data storage; and, processing large-scale data, running fast queries, and analyzing distributed datasets using Hadoop, Presto, and Athena. Hybrid role - 3 days per week in office. Up to 5% domestic travel required.