Scientist- Data and Modeler II USA

First Solar: 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 the design and statistical analysis of business initiatives and experiments. You'll work closely with business partners to identify needs and address issues. Using your expertise in statistics, data mining, and machine learning (e.g., predictive modeling, simulation), you will recognize patterns and generate insights from business data. Key responsibilities include designing, developing, and evaluating statistical and predictive models, and communicating findings and recommendations to management across various departments. You will also support implementation efforts.

Education and 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 in Data Science, Computer Science, Electrical Engineering, Applied Statistics, or Physics with 1+ years of relevant work experience in Data Science, Artificial Intelligence, or Machine Learning algorithm development.

Required Skills and Competencies

• Expertise in programming languages and statistical software tools (Python, SAS, R, JMP or similar), relational databases (SQL server), and data analysis and visualization software (preferably PowerBI, SAS).
• Experience with data science and machine learning packages such as Numpy, Pandas, Matplotlib, seaborn, bokeh, plotly.
• Solid understanding of machine learning models (regression, classification, neural networks, time series) and packages (Scikit-learn, Xgboost, Keras, Pytorch, Tensorflow, statsmodels).
• Deep knowledge of machine learning model tradeoffs such as hyper-parameter tuning, regularization, cross-validation, skewness in data, dimensionality reduction, and complexity vs interpretability.
• Experience 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) to design business experiments and measure the impact of business actions.
• Strong communication skills to work with groups, and capability to explain complex data relationships and results of statistical models to business stakeholders.
• Strong self-direction, initiative, and capability to prioritize multiple tasks from various requestors; demonstrated ability to manage multi-faceted projects.
• Excellent technical presentation skills.

Essential Responsibilities

• Work with business partners to identify and scope new opportunities for machine learning applications for process improvement.
• Collaborate with IT and Enterprise Data Management to define, secure, and prepare datasets for statistical modeling.
• Develop and deploy computer vision models (e.g., image classification, object detection, segmentation) to meet business needs.
• Explore data using various statistical techniques (e.g., data mining, regression, cluster analysis) to answer business questions or guide future model development.
• Create programs for running statistical tests on data and understanding the correlation of various attributes.
• Build hypotheses, identify research data attributes, and determine the best approach to address business issues.
• Apply advanced statistical techniques, including analysis of variance, t-tests, factor analysis, regression, and multivariate analyses or simulations, to analyze the effects of business initiatives.
• Develop predictive models (e.g., logistic regression, generalized linear models, autoencoders) as appropriate to support business objectives.
• Incorporate findings and provide insights as part of model development and enhancement.
• Prepare testing scenarios and test model performance.
• Research and stay updated on industry best practices and business strategies.
• Proactively introduce new and innovative ideas and approaches to develop business solutions.
• Perform other duties as assigned.

Reporting Relationships

Reports to Manager of Data Science and Analytics.

Travel

• Domestic and International travel as required.
• If