Digital Solutions Data Scientist

Location: Akron, OH, United States
Responsibilities 
  • Builds new predictive/descriptive models, evaluate current effectiveness of old models, design experiments/campaigns and analyze the resulting data, perform post-hoc (correlational) analysis when experimental designs (causational analyses) are not feasible and explains the limitations of the results, advises analytical data programmers on quality and infrastructure needs/challenges, etc.
  • Write code intended for automation of tasks.
  • Perform a few of these types of analysis depending on capability to satisfy the need of the organization and project:
    • Sample Selection / Stratification
    • Experimental Design
    • Categorical Data Analysis
    • Linear Regression
    • Non-Parametric Analysis
    • Multivariate Analysis
    • Time Series Analysis
    • Forecasting
    • Optimization
    • Simulation Models
    • Decision Trees
    • Heuristic Models
    • Algorithmic Models
  • Translating analytical results, presenting to manager level and below, and making recommendations for improvements in the areas of application
  • Create and present technical results to business managers.
  • Creates technical documentation of basic analyses.
  • Identifies and works with other analysts and engineers on data preparation issues (such as missing values and invalid data)
  • Applies basic techniques for handling interactions with limited involvement from other analysts and engineers
  • Perform medium scale statistical analysis or medium scale modeling projects independently or in collaboration with other analysts and engineers.
  • Depending on prior roles, may require formal training in some topical areas.
  • Partner with more experienced analysts and engineers on large scale modeling projects.
  • Technically supervising, mentoring, coaching, and training other analyst and engineers on advanced statistical techniques and how to apply them to business problems


Qualifications 
  • MS degree in Analytics, Statistics, or Mathematics fields and 2-4 years of Analytics experience, or industry experience equivalent.
  • Expertise acquired through prior experience in applying statistical/mathematical techniques in 1 or more business units/focus areas (R&D, Operations, Supply Chain, Pricing, Marketing, Credit Risk management).
  • Able to analyze technical data using 2 or more of the Statistical/Mathematical Specialties below:
    • Sample Selection / Stratification
    • Experimental Design
    • Categorical Data Analysis
    • Linear Regression
    • Non-Parametric Analysis
    • Multivariate Analysis
    • Time Series Analysis
    • Forecasting
    • Optimization
    • Simulation Models
    • Decision Trees
    • Heuristic Models
    • Algorithmic Models
  • Intermediate Statistical ability, able to apply techniques as appropriate for medium data sets with <= 50 variables (columns)
  • Must be a proficient storyteller able to explain complicated statistical analyses, techniques, and results to non-statistical audiences of Director-level Executives and below.
  • Capable of working and communicating directly with Manager-level and below to scope the technical needs of medium scale, medium-value projects and ad-hoc analyses.
  • Capable of assisting in the technical supervision and training of other analysts / data scientists / engineers
  • Capable of writing basic technical documents of small analytics without assistance.
 
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