Scientist- Data and Modeler II USA

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

Basic Job Functions:

• This position supports organizational strategy and operations through design and statistical analysis of business initiatives and experiments. Works with business partners to understand what the business needs and issues are to address. Applies knowledge of statistics, data mining, and machine learning (e.g., predictive modeling, simulation) or other mathematical techniques to recognize patterns and create insights from business data. Designs, develops, and evaluates statistical and predictive models that lead to business solutions. Communicates findings and recommendations to management across different departments. Supports implementation efforts.

Education/Experience:

• Bachelor’s degree in data science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 4+ years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development
• Master’s degree in data science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 2+ years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development
• PhD degree in Data Science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 1+ years of relevant work experience in in Data Science, Artificial Intelligence or Machine Learning algorithm development

Required Skills/Competencies:

• Proficient with programming languages and statistical software tools (Python, SAS, R, JMP or similar), relational databases (SQL server), data analysis and visualization software (preferably PowerBI, 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)
• 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.
• Knowledge of and experience with utilizing advanced descriptive statistics and analysis techniques (such as forecasting, analysis of variance, t-tests, categorical data analysis, nonparametric data analysis, cluster analysis, factor analysis and multivariate statistical analysis) design business experiments and measure the impact of business actions.
• Strong communication skills to work with groups, and experience with communicating business implications of complex data relationships and results of statistical models to multiple business partners.
• Strong self-direction, initiative, and ability to prioritize multiple tasks from various requestors, demonstrated ability to manage multi-faceted projects
• Excellent Technical Presentation Skills

Essential Responsibilities:

• Works with business partners to identify and scope new opportunities for machine learning applications for process improvement.
• Works internally and with IT and Enterprise Data Management to define, secure and prepare datasets for statistical modeling.
• Builds and deploys computer vision models (e.g., image classification, object detection, segmentation) to meet business needs.
• Explores data using a variety of statistical (e.g., data mining, regression, cluster analysis) techniques to answer business questions or guide future model development.
• Builds programs for running statistical tests on data and for understanding correlation of various attributes.
• Builds hypotheses, identifies research data attributes and determines best approach to address business issues.
• Applies advanced statistical techniques, including analysis of variance, t-tests, factor analysis, regression and multivariate analyses or simulation, to analyze the effects of business initiatives.
• Builds predictive models (e.g., logistic regression, generalized linear models, autoencoders) as appropriate to support business objectives.
• Incorporates findings and provides insights as part of model development and enhancement.
• Prepares testing scenarios and tests model performance.
• Researches and maintains awareness of industry best practices and business strategies.
• Proactively brings in new and innovative ideas and approaches to develop business solutions.
• Other duties as assigned. 
• Job description subject to change at any time.

Reporting Relationships:

• Reports to Manager of Data Science and Analytics

Travel:

• Domest