Scientist- Data and Modeler I USA

First Solar reserves the right to offer you a role most applicable to your experience and skillset. 

Basic Job Functions:

• The Data Scientist is responsible for the development, validation, and continuous improvement of models that accurately characterize the performance of First Solar photovoltaic products and systems. This position will achieve results through leadership of cross-functional teams to identify research needs, develop and execute analysis and test plans, and ensure quality of data collection, analysis and reporting.
• The position 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 Data Scientist will also be responsible for generating detailed energy predictions for prospective and operating sites.
• The position will build relationships with internal and external groups to research state of the art meteorological analysis, statistical analysis, energy prediction methods & tools, and recommendations for PV power plant design in support of their work. The position will be capable of independently identifying novel solutions to problems presented and communicating results to both a technical and non-technical audience.

Education/Experience:

• BS degree in Data Science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 2+ years of experience OR
• MS degree in Data Science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 1 year of experience.

Required Skills/Competencies:

• Proficient with programming languages (Python, Matlab, R, or similar), relational databases (SQL server), data analysis and visualization software's (preferably jmp, Tableau, SAS).
• Proficient with solar simulation software (PVSyst, PlantPredict, PV Sol, PV Design Pro or similar).
• 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)
• Have solid understanding of the machine learning model tradeoffs such as hyper-parameter tuning, regularization, cross-validation, skewness in data, dimensionality reduction, and complexity vs interpretability.
• Familiarity with renewables energy prediction modeling (preferably solar) and processing meteorological data and understanding of power engineering.
• 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;
• Demonstrated results in developing and delivering customer-facing technical collateral.
• Proficient use of all Microsoft Office suite programs.

Essential Responsibilities:

• Develop Artificial Intelligence/Machine Learning based algorithms such as energy prediction model, solar irradiance (GHI, POA) model, spectral correction model, device metastability model, and module degradation model to enable fast learning of product performance.
• 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. This will include familiarity with short term and long-term meteorological data sets and understanding industry accepted methods for interpolating data.
• Take ownership of data quality improvement in First Solar's field test sites. Assist in data analysis and state-of-the-art instrumentation and test equipment development.
• Support methods for verifying the capacity of installed solar PV systems and required customer reported pe