Responsibilities
- Engage with business partners and stakeholders to understand business problems and translate them into data science solutions.
- Coordinate and collaborate with data science, data engineering, analytic engineering, and other resources to achieve business goals.
- Work cross-functionally with finance, operations, and field engineering teams on opportunities for improved insights.
- Lead and contribute to the end-to-end development and deployment of predictive and prescriptive models.
- Explore large datasets using modeling, analysis, and visualization techniques.
- Communicate results, analyses, and methodologies to technical and non-technical senior level stakeholders.
- Ability to mentor, coach, and lead others.
- Contribute to and help build ML/AI vision to support business strategy.
Required Knowledge, Skills, Abilities (Qualifications)
- Degree in Data Science, Machine Learning, Applied Mathematics/Statistics, or a related field.
- 3-5 years of experience applying data science, AI/machine learning, and analytics techniques to business problems.
- Experience leading data science projects.
- Experience with supervised and unsupervised machine modeling techniques, with a focus on time-series forecasting.
- Experience solving real-world problems using programming languages such as SQL, Spark, and Python, and deploying solutions to enterprise systems.
- Excellent strategic thinking, communication, collaboration, and problem-solving skills, including working with and articulating results to senior business stakeholders.