Date: February 12, 2018

Warren Averett Staffing & Recruiting is seeking an entry level Business Intelligence Analyst for a growing client in the Huntsville, Alabama area. The ideal candidate would be a recent graduate with a Bachelor's Degree in Statistics or Marketing (or in graduate classes). Additionally, the ideal candidate will possess advanced computer skills in Excel and SQL database and intermediate programming skills.

Responsibilities

  • Responsible for centralized data management, including cleansing, validation, analysis and migration.
  • Develop analytic solutions to produce timely, accurate, user-friendly and actionable information that can be understood by multiple audiences and immediately applied to answer key business questions.
  • Exhibit a wide range of technical knowledge including database, application development, agile project management scheduling, etc.
  • Define goals, objectives, strategies and standards for data cleansing/validation/ accuracy.
  • Develop data assets for advanced analytics that are reusable, agile and multi-purposed
  • Identify, analyze, cleanse, reformat, integrate, transform and structure data from internal and external sources.
  • Streamline and operationalize data assets into the business workflow
  • Apply descriptive analytics to analyze data and validate assumptions, understand and articulate results to a narrow audience.
  • Identify, select and extracts relevant data from various internal and external sources
  • Manipulates and monitors raw data sets into information fit for analysis independently.
  • Utilizes established best practices around descriptive analytics
  • Work with colleagues, partner organizations and clients in a collaborative and responsible manner, to understand issues from both business and technical perspectives and determine the best data analytics solutions
  • Independently determine which quantitative tools/approaches and data sources to use to address analytic questions, while selecting and designing tools that allow reuse of design components between projects and clients
  • Critically review analytic results and final work product and continually work to improve the quality and efficiency of work processes and products, including improving the validity of analytic results
  • To the extent possible and appropriate, automate processes to make future analysis more efficient
  • Monitor and anticipate industry and academic news to identify and apply trends and best practices
  • Develop and communicate goals, strategies, tactics, project plans, timelines and key performance metrics to reach goals.
  • Knowledge of data modeling
  • Knowledge of data mining and predictive modeling (e.g., regression, segmentation, machine learning, SEM, MCMC, Bayesian, boosting, cross-validation)
  • Knowledge of collaborative filtering and recommender systems
  • Knowledge of social network analysis and statistical text mining
  • Knowledge of event detection and tracking
  • Knowledge of cluster analysis, probabilistic modeling, anomaly detection.
  • Demonstrated ability to learn from mistakes, apply constructive feedback to improve performance, and share appropriate feedback with team members
  • Excellent analytical and problem solving skills – the ability to work on complex problems where analysis of situations requires an in-depth evaluation of various factors, anticipate the downstream impact of change on product design, identify key requirements, develop alternative solutions, and focus on small details and the big picture simultaneously

Requirements

  • Bachelor’s Degree in STEM (Science, Technology, Engineering, or Mathematics.
  • Graduate students and Master's Degree is preferred.
  • Experience in Descriptive Analytics is preferred.
  • Advanced Computer Skills in Excel, SQL database languages, programming & Python, R, and statistical design.
  • Experience using a data visualization software such as PowerBI or Tableau would be a plus.
  • Strong interpersonal skills to work as part of a team.
  • Willingness to be open to learning, mentoring, and growing.

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