Engineer- Analytics III USA

First Solar reserves the right to offer you a role most applicable to your experience and skillset. Basic Job Functions: The Analytics Engineer III is responsible for the development, validation, and continuous improvement of methodologies that accurately characterize the performance of First Solar photovoltaic products and systems. He/she will achieve results through leadership of cross-functional teams to identify research needs, develop and execute methods and test plans, and ensure quality of data collection, analysis, and reporting. The successful candidate will be able to adapt quickly to new data and analytical requests from across the First Solar organization. This may include engineering statistical analysis, contract analysis, policy analysis and project management tasks. The ideal candidate will build relationships with internal and external groups to research state of the art field performance measurements of solar photovoltaic products, meteorological analysis, statistical analysis, and energy prediction methods & tools. He/she will be capable of independently identifying novel solutions to problems presented and communicating results to both a technical and non-technical audience. Education/Experience: At least 3 years in a Photovoltaics, Power Engineering, or other renewable energy field At least 3 years in physical/technical data analysis Advanced degree in Materials Science, Physics or Electrical Engineering required. PhD preferred. Required Skills/Competencies: In-depth understanding of solar PV device behaviors and field performance of various technologies. Familiarity with renewables energy prediction modeling (preferably solar) and processing meteorological data and understanding of power engineering. Proficient with solar simulation software (PVSyst, PlantPredict, PV Sol, PV Design Pro or similar). Proficient with programming languages (Python, Matlab, R, or similar), relational databases (SQL server), data analysis and visualization software's (preferably jmp, Tableau, SAS). Experienced with standard data science and machine learning packages such as Numpy, Pandas, Matplotlib, seaborn, bokeh, plotly. Have solid understanding of the machine learning model stack (regression, classification, neural networks, time series) and packages (Scikit learn, Xgboost, Keras, Pytorch, Tensorflow, statsmodels). Excellent communication, organization and interpersonal skills, comfortable to interpret data and modeling efforts to a large audience on a regular basis and publish results in reputed PV conference and journals. Strong self-direction, initiative, and ability to prioritize multiple tasks from various requestors, demonstrated ability to manage multi-faceted projects. Proficient use of all Microsoft Office suite programs. Essential Responsibilities: Develop solar module device characterization methods. Design, plan and execute testing to evaluate module performance to obtain competitive knowledge and insights. Forecast/Model long-term energy performance of First Solar modules in production/field environments, perform model vs actual analysis on a periodic basis. Identify areas of improvement in the models. Validate model predictions with measured data from plant monitoring systems and field test results. Evaluate the feasibility of new products, model energy performance of new module technologies under various meteorological climates, improve model through successive iterations, ensemble results to develop a robust model and validate model prediction with testbed before production deployment. Use advanced analytics tools such as Python, R, and Matlab to automate data analysis. Write and document reusable scripts with a mix of API's and packages. Develop methods to determine the statistical level of certainty around the quantity and quality of solar insolation at various project sites. T