Sr Manager - Data Science

First Solar (US)OH, OH
Onsite

About The Position

This position manages 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 advanced knowledge of statistics and data mining (e.g., predictive modelling, 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. Serves as lead statistician for the unit, providing expertise, oversight, and guidance on statistical analysis efforts. Communicate findings and recommendations to management across different departments. Supports implementation efforts. Should lead and mentor the team working in the Data Competency Centre.

Requirements

  • Bachelor’s degree in data science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 8-10 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 5+ 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 4+ years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development.
  • Working knowledge of budgets and financial statements.
  • Demonstrated skill of managing teams; Ability to coach and mentor team members to drive results.
  • Demonstrated experience 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).
  • Demonstrated experience with standard data science and machine learning packages such as Numpy, Pandas, Matplotlib, seaborn, bokeh, plotly.
  • Demonstrated experience with the machine learning model stack (regression, classification, neural networks, time series) and packages (Scikit learn, Xgboost, Keras, Pytorch, Tensorflow, statsmodels).
  • Demonstrated experience of the machine learning model tradeoffs such as hyper-parameter tuning, regularization, cross-validation, skewness in data, dimensionality reduction, and complexity vs interpretability.
  • Demonstrated 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.
  • Demonstrated experience with computer vision models (e.g. image classification, object detection, and segmentation).
  • Demonstrated experience working with various business partners to scope and design the statistical framework for business solutions and socialize and help integrate results.
  • 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.

Responsibilities

  • Statistical Analysis & Model Development: Works with business partners to identify and scope new opportunities for statistical analysis applications to evaluate business performance and to support business decisions. Works internally and with I/S and Enterprise Data Management to define, secure and prepare datasets for statistical modeling. Explores data using a variety of statistical (e.g., data mining, regression, cluster analysis) techniques to answer business questions or guide future model development. Build programs for running statistical tests on data and for understanding correlation of various attributes. Builds hypotheses, identifies research data attributes and determines the best approach to address business issues. Working with business partners leads development of experimental design for business initiatives. 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. Build predictive models (e.g. logistic regression, generalized linear models) as appropriate to support business partner objectives. Build and deploy computer vision models (e.g., image classification, object detection, segmentation) to meet business needs. Prepares testing scenarios and tests model performance. Incorporates findings and provides insights as part of model development and enhancement. Provides guidance and direction related to statistical analysis to less experienced Data Science & Analytics staff as needed. Provides peer review related to analytics methods and results. Responsible for advanced analytics, including experimental design and analysis, for the most complex business experiments.
  • Model Consultation, Implementation, & Communication: Serves as statistical expert within the unit as well as in consultation to various areas of the business, to support design and analysis of business experiments. Leads analytics projects or components related to large, complex business initiatives. Prepare recommendations and findings for business partners. Works with research and analytics staff and other areas of the business on model application and implementation. Effectively communicates and delivers statistical and predictive model results to business partners, supporting socialization and adoption of analysis results into business activities and decisions. Assists with knowledge transfer and training to business areas regarding new analytics applications as part of implementation process. Works closely with business stakeholders to identify and answer critical questions. Assists in the development of standard analytical approaches and methodologies for the department. Provides knowledge transfer and training on new modeling and statistical analysis tools and methodologies to less experienced staff.
  • Industry Research: Research and maintain awareness of industry’s best practices and business strategies. Proactively brings in new and innovative ideas and approaches to develop business solutions. Research and leverage new statistical techniques and technologies to apply in their statistical research work.
  • Other duties as assigned.
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