The Lead Data Scientist works independently on all phases of an analytics project. The scope of work includes the data analysis and preparation, model development, and the presentation of results and recommendations to stakeholders.
Cox Enterprises is a family-run operation that began nearly 120 years ago. As part of this great family business, we treat our team members and clients like they’re just that — family. This atmosphere has been instrumental to our success and has shaped our willingness to fuel epic innovation, drive unprecedented growth and deliver the mind-blowing, needle-moving, connected experience we promise.
Cox Automotive is transforming the way the world buys, sells and owns cars. Come join the transformation!
Technology We Use:
Python, SAS, SQL, AWS
Primary Responsibilities and Essential Functions:
- Work independently on all phases of an analytics project, including formulation, research, development, implementation, testing, and maintenance.
- Assist with problem formulation and the selection of an appropriate methodology.
- Present findings and recommendations to stakeholders.
- Maintain an awareness of trends in the field; research and suggest new methodologies.
Required Experience (minimum):
- Degree in Statistics, Operations Research, Applied Mathematics, Computer Science, Economics, or related quantitative field.
- BA/BS degree in related field and 7+ years of experience; or an equivalent combination of education and work related experience.
- Strong problem-solving skills with an emphasis on product development.
- A drive to learn and master new technologies and techniques.
- Proven experience applying descriptive, predictive, and prescriptive statistics to real-world problems.
- Experience querying relational databases using SQL.
- Ability to develop and maintain production-ready code.
- Experience working with Amazon Web Services (AWS) strongly preferred.
- The ability to present findings clearly and concisely to team members and data science leadership.
- The ability and inclination to coach junior staff.
What We Look For (preferred):
- Expertise in one or more of the following strongly preferred:
- Generalized linear models, time series models, forecasting techniques, cluster analysis, and principle component analysis.
- Linear and mixed integer optimization, discrete event simulation, heuristic methods, and network flow analysis.
- Machine Learning: Selecting, tuning, and implementing a variety of common supervised and unsupervised models, including decision trees, nearest neighbor models, and neural nets; and several standard ML libraries, such as scikit-learn, TensorFlow, or similar.