Data Scientist enhancing merchandising and inventory performance using machine learning techniques at Nordstrom. Collaborating with teams to develop data - driven solutions for better customer experiences.
About the role
- Principal Data Scientist improving PG&E’s wildfire risk management through predictive analytics and machine learning. Collaborating with stakeholders and driving data science innovation in electric operations.
Responsibilities
- Creates, applies, and evaluates advanced data mining architectures / models / protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data sets
- Applies and evaluates data science/ machine learning/artificial intelligence methods to develop defensible and reproducible predictive or optimization models that involve multiple facets and iterations in algorithm development.
- Writes and documents complex and reusable python functions as well as multi-modular python code for data science.
- As a technical leader, provides thought leadership in the use of a ML algorithms for solving business problems.
- Mentors junior data scientists and drives standardization in process and toolsets across the data science community at PG&E.
- Collaborates with analytics platform owners to prioritize and drive development of scalable data science capabilities.
- Acts as peer reviewer for complex models/AI algorithm proposals.
- Recognizes and prioritizes the most important work related to data science models to achieve highest operational and strategic impact for analytics in the business.
- Works with enterprise leaders as an advocate for digital transformation of the business through the adoption of data science, analytics, and data-driven business processes.
- Presents findings and makes recommendations to executive leadership and cross-functional management.
Requirements
- Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics, or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
- 8 years in data science OR 2 years, if possess Doctoral Degree or higher, as described above
- Experience in utility and energy industries
- Thought leadership in the external data science/artificial intelligence/machine learning community of practice, as demonstrated through peer reviewed journal publications, intellectual property/patent achievements, conference presentations, volunteering in professional organizations for the advancement of the field, participation in externally sponsored research projects, open source contributions, or similar activities.
- Proficiency with data science standards and processes (model evaluation, optimization, feature engineering, etc) along with best practices to implement them.
- Proficiency with commonly used data science programming languages, packages, and software tools for building data science/machine learning models and algorithms
- Mastery in explaining in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines.
- Ability to clearly communicate complex technical details and insights to colleagues, stakeholders, and leadership
- Leadership in developing, coaching, teaching and mentoring others to meet both their career goals and the organization goals.
Benefits
- This job is also eligible to participate in PG&E’s discretionary incentive compensation programs.
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