Scientist- Data Research and Development USA

About the role

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.

Responsibilities

• Development Program Statistical Research & Meta-analysis (70%)
  • 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.
  • Define experiment’s statement of intent, reviewing previous responses and assuring factor estimability is understood.
  • Systematically review 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.
• Data Science & Statistics Subject Matter Expert (30%)
  • 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.

Qualifications

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

Skills

• 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.