Scientist- Data Research and Development USA

First Solar (US)•Perrysburg, OH

7d•$91,200 - $130,000•Onsite

About The Position

This position supports large scale statistical experiment design and analysis to evaluate innovative ideas on thin-film processes. You will join many disparate data sources to compile an integrated story of discovery, within and across experiments, projects, and people. You will apply an advanced knowledge of statistics and data science techniques to recognize patterns and create insights in a state-of-the-art R&D solar fabrication facility. Design, develop, and evaluate experimental models that point in the direction of maximum success. Serve as lead statistician for project teams, providing expertise, oversight, and guidance on analysis efforts. Provide support, training, and direction to all Advanced Research Engineers on DOE, statistical analysis, and modeling. Help your colleagues build a world and workplace that is just sustainable, and equitable.

Requirements

Bachelor’s Degree in Computer Science, Information Systems, Engineering, Data Science, or similar technical discipline, and 5 years of relevant technical experience or 2 years of experience as an Engineer- Analytics R&D at First Solar.
Master’s Degree in Computer Science, Information Systems, Engineering, Data Science, or similar technical discipline, and 3 years of relevant technical experience or 2 years of experience as an Engineer- Analytics R&D at First Solar.
Ph.D. in Computer Science, Information Systems, Engineering, Data Science, or similar technical discipline, without prior technical work experience.
Deep understanding of Design of Experiments.
Meta-analysis and systematic research review.
Data forensics and partitioning on large data sets.
Data Wrangling: preparation, mapping, and transformation.
Structured and unstructured data sets.
Executive level storytelling with data visualization.
Impart clarity when communicating complex data relationships.
Linear Algebra: Matrix Algebra and eigenvalues/vectors.
Passion to learn new areas of study (device physics learning will be intensive).
High emotional intelligence.
Bravery to speak a dissenting opinion or present evidence against current belief.
Skilled in a structured problem-solving method (such as DMAIC, A3, 5 Whys, etc.).
Extensive understanding of Probability and Inferential Statistics as well as visual display of these concepts.
Expert at building predictive models and utilizing advanced statistical analysis, including generalized linear models, decision trees, PCA, logistic and multivariate regression.
Deep knowledge of statistical and modeling software tools and scripting languages such as JMP, SAS, Python, SPSS, or R to manipulate data and draw insights from large data sets.
Experience with Microsoft environment: Windows OS, Office 365, Teams, SharePoint, etc.

Nice To Haves

Previous R&D, PV, or Semiconductor experience helpful, but not necessary.

Responsibilities

While assigned to a Development Program, serve as statistical expert and work with Technical, Operations and Process Engineering Teams to achieve program goals via research, modeling, experiment design and analysis.
Gain deep understanding of program objectives, learning the physics behind the processes to know current and predict future Program Team needs.
Help Team define an experiment’s statement of intent, reviewing previous responses and assuring factor estimability is understood.
Systematic review of prior experimentation to find relevant, high-quality data, while accounting for variability in study approach, sample size, execution, environment, etc.
Standardize and weight prior research to build new predictive models to guide Program experimentation.
Understand experimenter’s needs and develop custom experiment design to efficiently create insight.
Exhaustively evaluate experiment design and resulting model.
Work with Program Partners to define and prepare datasets for modeling.
Monitor many data streams and feedback data quality to Program Teams.
Be the data forensics Program Lead, data mining root cause of un-intended processing artifacts.
Explore data using a variety of statistical (e.g., data mining, regression, cluster analysis, partitioning, PCA) techniques to answer research questions and guide future experiments.
Synthesize independent experiment findings into overall treatment effects.
Prepare testing scenarios and test model performance against new results, subsets, etc.
Clearly and concisely communicate analysis and modeling results to business partners, supporting socialization and adoption of results into business activities and decisions.
Perform Program meta-analysis, putting the newest experiment in context with history, highlighting key abnormalities, consistencies, and correlations.
Define data structures and systems that will institutionalize improvements and lower the bar for analysis across the organization.
Hone and proliferate the craft of cross-experiment meta-analysis in Research & Development.
Assist in development of standard analytical approaches and methodologies for the department.
Apply advanced statistical techniques, including analysis of variance, t-tests, factor analysis, regression, multivariate analyses, PCA or simulation, to analyze the effects of experimentation.
Provide guidance and direction related to statistical analysis to less experienced Research & Development staff as needed.
Provide peer review related to analytics methods and results.
Work closely with Development Technical Teams to identify and answer critical questions.
Identify and scope new opportunities for statistical analysis applications and scripting.
Proactively research and leverage new statistical techniques and technologies to apply and teach.
Develop and lead training sessions for advanced Data Science & Statistics concepts.
Other duties as assigned.