Sr. Data Scientist (Sr. Advisor)

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About IT
The role of IT goes beyond the traditional Information Technology"service provider." Many of the innovative ideas and projects that shape thecompany's future and move SCE forward are dependent on technology. IT employeesare at the heart of these projects, collaborating, designing and executingtechnology solutions that are transforming our industry.
Position overview
The Sr.Data Scientist will work closely with clients, data stewards & SME's,information architects, data engineers, project/program managers, and otherteams to turn data into critical information and knowledge that can be used tomake sound business decisions. This includes providing data that is congruentand reliable. They need to be creative thinkers and propose innovative ways tolook at problems by using data mining (the process of discovering new patternsfrom large datasets) approaches on the set of information available. They willneed to validate their findings using an experimental and iterative approach.Also, Data Scientists will need to be able to present back their findings tothe business by exposing their assumptions, validation and work in a way thatcan be understood by their business counterparts.
The Data Scientist is responsible for modelingcomplex analytical problems, discovering insights and identifying opportunitiesthrough the use of statistical, algorithmic, mining and visualizationtechniques. In addition to advanced analytical skills, the individuals in thisrole should be proficient at integrating and preparing large, varied datasets,overseeing advanced analytical solutions development and communicating results.
Typical responsibilities willinclude:
UseCase Understanding: Works with senior SCE stakeholders to understand businessproblems, goals and objectives, translate them into data science projects andappropriately prioritize. Work closelywith business, engineering and technology teams to develop solution todata-intensive business problems. Supervise internal and external science teams. Perform quality control of deliverables.Prepare reports and presentations, and communicate with executives. Providethought leadership in algorithmic and process innovations, and creativity insolving unconventional problems.
DataRequirements: Identify what data is available and relevant, including internaland external data sources; leverage new data collection processes such as smartmeters, SCADA, and social media; Collaborate with information architects andData Stewards/SME's to select relevant sources of information; Make strategicrecommendations on data collection, preparation, integration, quality,exploration, and retention.
DataPreparation: Facilitate selection and preparation of data to be used forspecific use cases; Develop and recommend data sampling techniques; Developdata cleaning specifications and approaches. Apply missing data treatments as needed. Develop and/or implement tools for data acquisition, extraction,transformation, management, and manipulation of large and complex data sets.Explore, model, mine, and experiment with data to answer critical businessissues.
Modeling & Deployment: Design, develop andevaluate highly innovative models for predictive learning. Establish scalable,efficient, automated processes for large scale data analyses, modeldevelopment, model validation and model implementation. Use machine learning,data mining and statistical techniques to create new, scalable solutions forbusiness problems. Translate business problems into mathematical problems. Perform variable selection and other standardmodeling tasks. Develop simplevisualizations of results. Produce modelperformance metrics. Prepare deliverable reports for business teams

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