Data Modeler

  • Negotiable
  • Jacksonville, FL, USA
  • Permanent, Full time
  • Florida Blue
  • 22 Sep 17

Develop propensity models based on campaign response, lead distribution, customer attrition, and cross selling opportunities.

Job description

  • Develop database specifications for segmentation, targeting, fulfillment, data enhancement, contact data set creation and relationship marketing campaign programming.
  • Track, report, and analyze data to recommend retention strategies, acquisition strategies, and maximization of customer lifetime value through effective use of relationship marketing.
  • Extract and aggregate consumer data as needed for model development.
  • Perform exploratory data analysis, data cleansing, and data visualization using data mining tools.
  • Develop and apply data transformations and derivations to support downstream modeling initiatives.
  • Utilize statistical/data mining techniques (e.g. clustering, missing value patterns) to impute missing values in modeling datasets.
  • Score consumer data sets and campaign lists for effectiveness and optimized sales results, as needed.
  • Translate business needs to data elements in the Marketing Database and other data marts to source, extract, match and modify data to enable modeling efforts.
  • Develop and validate multiple models (e.g., Decision Trees, Logistic Regression, Neural Networks) to address business problems.
  • Utilize profit matrices to maximize ROI on models.
  • Develop, document, and maintain standards for campaign data storage and retrieval within multiple systems to ensure consistency and integrity of all data used for business modeling and forecasting.

Consult and advise campaign teams on how to increase efficiencies of direct marketing based on modeling.

  • Develop reports and presentations documenting analyses and ensuring that key stakeholders understand the business implications for those analyses.
  • Use model selection techniques (e.g., Life/ROC curves) to identify and deploy the best model.
  • Recommend appropriate statistical solutions to business problems to ensure the effectiveness of marketing target audience list.
  • Determine and recommend models (predictive models) that can be used to improve efficiencies of direct marketing, customer retention, and cross sell opportunities/results.

Identify and recommend improvements to enable increased campaign results.

  • Identify, investigate, and document possible root causes of trends, issues, and performance gaps based on analyses and campaign results to determine improvements and recommendations.
  • Monitor and evaluate progress of improvement initiatives through conclusions including the impact of the predictive models on the marketing campaign results.
  • Job Requirements
  • Bachelor's degree in Statistics, Mathematics, Finance or related field or equivalent work experience.
  • Minimum of 5 years experience in marketing science, statistical analysis, market response modeling, data mining, business modeling and forecasting.



Advance

  • Experience in database marketing capabilities and relational database architectures.
  • Demonstrated relationship skills, active listening skills, and the ability to understand, translate, and communicate marketing and data concepts.
  • Ability to track, to report, and to analyze data/results and make strategy recommendations for multi-facet, complex direct-marketing campaigns.
  • Ability to leverage reporting, analytical, and data mining software tools, e.g. statistical software and databases - SAS, SAS Enterprise Miner and SQL.
  • Ability to use statistical mining techniques, e.g. Decision Trees, Logistic Regression, Neural Networks, Clustering, Missing Value Patterns.
  • Ability to use model selection techniques, e.g. Lift/ROC curves.
  • Ability to manage multiple projects simultaneously.
  • Strong attention to detail.



Intermediate

  • Proven ability to build relationships within the business area, across the organization, and external to BCBSF.
  • Knowledge of project management.
  • Ability to use MicroSoft Office, e.g. Word, Excel, PowerPoint, Access
  • Knowledge of CQI tools and techniques, i.e. Six Sigma.
  • Preferred Specifications
  • Experience using R for data mining.
  • Experience in the health care industry.
  • Knowledge of heath care products.
  • Yellow-belt certification.
  • Masters degree in Statistics, Mathematics or a related field