Engineer- Analytics II USA

First Solar (US) • Perrysburg, OH

19h • Onsite

About The Position

The Analytics Engineer II 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 Simulator IV measurements, third party lab validation, 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.

Requirements

• Bachelor’s degree in Materials Science, Physics or Electrical Engineering with 5-8 years of relevant work experience in a manufacturing and/or research environment with related statistical analysis, data mining and technical leadership skills. OR Masters degree in Materials Science, Physics or Electrical Engineering with 2-5 years of relevant work experience in a manufacturing and/or research environment with related statistical analysis, data mining and technical leadership skills. OR PhD degree in Materials Science, Physics or Electrical Engineering with 0-3 years of relevant work experience in a manufacturing and/or research environment with related statistical analysis, data mining and technical leadership skills
• At least 3 years in a Photovoltaics, Power Engineering, or other renewable energy field.
• At least 3 years in working with PV Solar Third Party Agencies.
• At least 3 years in physical/technical data analysis.
• Familiar with solar PV module IV characterization, Solar Simulator Calibration, Third Party Lab collaboration.
• In-depth understanding of solar PV device behaviors and field performance of various technologies.
• 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)
• 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

Responsibilities

• Develop solar module device characterization methods
• Collaborate with third party labs for external validation.
• 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. This will include familiarity with short term and long term meteorological data sets and understanding industry accepted methods for interpolating data.
• Other duties as assigned.
• Job description subject to change at any time.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees