Manager, Data Science

Job Description

• Build, implement and maintain a variety of linear and nonlinear predictive models
• Perform basic and advanced feature engineering on new and existing datasets
• Turn vaguely defined business needs/problems into problem definitions through statistical methods and provide answers through data exploration
• Create datasets and perform analyses to solve business problems and provide actionable recommendations
• Create visuals and/or dashboards to monitor changes to the portfolio over time and communicate these changes to the executive team
• Complete any ad-hoc analyses or projects that contribute to the quality of the data used and effectiveness of the data science team in general
• Provide input on the strategy and direction of data science team and projects

• Experience with some of the following is a must:
  • Python - pandas, numpy, scikit-learn
  • Anaconda, Jupyter notebooks
  • R - dplyr, ggplot, lm, etc.
  • Version control systems (Git/GitHub)
  • SQL, PostgreSQL
  • Docker
  • Shell scripting/command line tools
  • Python development
• Data visualization and exploration
• Math & statistics
• Multivariate analysis
• Predictive modeling
• Linear & logistic regression
• Classification trees and random forests
• Unsupervised learning – clustering, principal component analysis
• Effective problem-solving skill
• Detail-oriented and methodical
• Ability to communicate analysis approaches and results in an organized and clear way
• Strong multitasking skills and ability to work under pressure on several projects at a time.
• Flexible and willing/able to learn new tools/methods quickly
• Good organization and time management skills and the ability to set priorities and accomplish objectives to meet deadlines in a fast-paced environment.
• Ability to model and promote ethical behavior.
• Ability to extrapolate from historical data and current events to anticipate business needs and plan accordingly.
• Self-starter and able to identify areas of need and jump in where needed and necessary.
• Ability to drive projects to completion independently
• Eager for new challenges and coordination with a number of different stakeholders within the organization.
• Completed a Bachelor’s degree or equivalent in a STEM field, such as Mathematics, Statistics, Applied Statistics, Data Science, or Analytics
• Masters or Ph.D. preferred