Senior Statistical Analyst

Location: Nashville, TN
  • ​MS degree in Analytics, Statistics, or Mathematics fields and 6-9 years of Analytics experience or PhD degree and 4-7 years of Analytics experience
  • 3+ years of SAS programming experience in previous roles (SAS not substitutable with any other programming language).
  • Expertise acquired through prior experience in applying statistical/mathematical techniques in 2 or more business units/focus areas (Operations, Supply Chain, Real-Estate, Pricing, Marketing, Credit Risk management).
  • Able to analyze business data using 3 or more of the Statistical/Mathematical Specialties
  • Statistically Advanced able to apply techniques as appropriate for moderate data sets with <= 100 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 Director-level Executives and below to scope the technical needs of large scale, high-value, technically complex projects and medium scale ad-hock analyses.
  • Capable of assisting in the developing, training, mentoring, and technically supervising all more junior level Statistical Analysts / Data Scientists
  • Capable of writing technical documents of intermediate analytics without assistance. 

  • 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.
  • Majority of time spent coding is on creation of new code
  • Write large blocks of code that will be run repetitively with moderate efficiency
  • Perform several 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
  • Survey Design and Analysis
  • Survival Analysis
  • Time Series Analysis
  • Forecasting
  • Optimization
  • Simulation Models
  • Decision Trees
  • Heuristic Models
  • Algorithmic Models
  • Translating analytical results, presenting to Director-Level executives and below, and making recommendations for improvements in the areas of application
  • Creation of intermediate technical documentation
  • Identifies and with limited involvement from more experienced analysts resolves data issues (such as missing values and invalid data)
  • Creates basic transformations of data independently and intermediate transformations with limited involvement from more experienced analysts
  • Applies basic techniques for handling small sample sizes independently and applies intermediate techniques with limited involvement from more experienced analysts
  • Perform large scale statistical analysis or medium scale modeling projects independently or in collaboration with other Analysts.
  • Apply skills learned in previous roles to the business using SAS.
  • Mentors less experienced Analysts, and interacts professionally with leaders outside of Analytics.
  • Depending on teaching proficiency, formally train or assist in the formal training of less experienced Analysts.
  • Partner with more experienced Analysts on large scale modeling projects.
  • Technically supervising, mentoring, coaching, and training all less senior analysts on advanced statistical techniques and how to apply them to business problems
  • Assist Associate Director and Director of Analytics in the identification and quantification of applications of analytics and development of project charters and plans as appropriate​
Tami Andrade Fitzpatrick
Senior Recruiter
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