Regardless of whether you want to work for a start-up, a large company, or a non-profit, your employer’s “analytics operating model” will be a critical part of both expectations, and your ability to succeed. Are data scientists expected to develop their own pipelines? Do data engineers sit with line of business project teams, or with IT peers? Are there documented developer best practices and how strictly are these enforced? Attendees will be provided the opportunity to develop an understanding of common analytics operating models, and how their personal skills and working style may match or clash with such models.
Creating an Analytics Operating Model for Success
JP Dolphin has received grants from the DOE, EPA, and the IEEE to install and develop technologies to improve the efficiency of renewable energy installations domestically and abroad at all stages of the value chain. His private sector experience includes being a founding member of the Google-Duke Carbon Offset Initiative and working on the Strategy team at Chevron Energy Solutions, the company’s renewable energy division.
He is currently the Manager of PG&E's Strategic Data Science team, whose mission is to apply industry-leading data science to PG&E’s largest data sets with the goal of improving operational efficiency and informing strategic decision making. JP was a Deans’ Scholar at Harvard where he earned a Masters in Sustainability. He is an avid fan of Duke Basketball, his alma mater. JP lives in San Francisco with his wife, Rachel, and dog, Winston.