Data Scientist Manager
Play an integral role in supporting modeling and data analysis and database needs for assigned line of business. Manage the creation and/or usage of large data sets, providing information-based decision logic and predictive modeling solutions, and translates modeling/analytic output into understandable/actionable business knowledge, insight and applications. Demonstrate strong technical/problem solving skills. Support multiple projects collaboratively. Responsibilities
- Identify, develop and implement complex analytical solutions leveraging tools such as predictive modeling, advanced machine learning techniques, simulation, optimization solutions, etc..
- Manage dataset creation including data extraction, derived and dependent variable creation, and data quality control processes for analytics, model development, and validation. May monitor execution of analytical solutions, including criteria specification, data sourcing, segmentation, analytics, selection, delivery, and back-end data capture results.
- Under direction of the Sr. Leader, collaborate with business leaders and/or analysts to provide analytical thought leadership and support for business problems. Identify and interpret business needs, define high-level business requirements, strategy, technical risks, and scope. Develop, document, and communicate business-driven analytic solutions and capabilities, translating modeling and analytic output into understandable and actionable business knowledge.
- Embed analytic programs and tools. Ensure continued accuracy, relevancy, and effectiveness and track process improvements once deployed.
- Ensure adherence to data and model governance standards that are set and enforced by industry standards and/or enterprise and business unit data governance polices and leaders.
- Contribute to ongoing expansion of data science expertise and credentials by keeping up with industry best practices, developing new skills, and knowledge sharing. Work cross functionally to develop standardized/automated solutions and adopt best practices.
- Masters degree or equivalent in Quantitative Discipline (i.e. Finance, Statistics, Computer Science, Actuarial Science, Economics, Engineering, etc.).
- 3-5 years relative experience.
- Knowledge of advanced statistical concepts and techniques; skilled in linear algebra.
- Experience conducting hands-on analytics projects using advanced statistical methods such as generalized regression models, Bayesian methods, random forest, gradient boosting, neural networks, machine learning, clustering, or similar methodologies.
- Experience with statistical programming (Python,R, SAS SQL etc.) & data visualization software in a data-rich environment.
- Experience in AWS services such as Redshift, S3, Sagemaker will be an advantage.
- Proven ability to present/communicate complex, technical materials in a way that facilitates decision making and drives outcomes; ability to communicate to less technical partners.
- Proven ability to apply both strategic and analytic techniques to provide business solutions and recommendations.
- Ability to work effectively in a collaborative team environment.