Our Client is a leading provider of innovative data-driven products and solutions. Their robust analytics and broad range of customer segmentation and statistical modeling methodologies, combined with the firm’s unique approach to data analysis illustrates their position as a forerunner in this space.
- Develop predictive analytic solutions/statistical models for utilization by analytics and marketing teams in targeting new customers, and optimizing existing customers.
- Develop statistical forecasting models and tools, including response modeling, linear/logistic regression modeling, decision trees, customer survival modeling, proportional hazards modeling, time series modeling, uplift modeling, and experimental design to analyze, interpret, and summarize data for use in customer management strategies.
- Constructs the architecture around the model development process and the associated data management.
- Deliver data-driven insights about customer behavior, conversion and engagement
- Apply statistical theory and methods; Identify relationships and trends in data, and apply results to address business challenges.
- Increase knowledge of consumer intent, behavior, and experiences through the identification of new analytics tools to mine consumer behavior and assess performance
- Create performance metrics and tracking processes to measure the effectiveness of the predictive modeling efforts.
- Communicate analytical results to cross-functional team members.
- Identify cutting edge statistical tools/techniques and work with modelers/analysts to incorporate methodology into existing analytics.
- 8-10 plus years professional experience developing statistical models, segmentation schemes and data-driven analyses.
- Advanced degree in a quantitative/applied field: statistics, operations research, mathematics or econometrics. Ph.D preferred.
- Proficiency in handling large datasets and using statistical modeling techniques and tools including linear regression, logistic regression, ANOVA/ANCOVA, time series modeling, segmentation, decision tree, cluster analysis, factor analysis, survival analysis and simulation based analysis. Excellent SAS and CHAID skills required.
- Expertise performing exploratory data analysis and implementing propensity models
- Advanced experience with experimental research/test design.
- Knowledge of direct marketing/database marketing analytics, tools and methodologies for B2C preferred.
- Proven track record of independent thinking & ingenuous approaches to problem solving
- Ability to work in a team environment – to brainstorm and exchange ideas
- Proven track record of building new & innovative analytic tools.
Please send resumes to: firstname.lastname@example.org and reference job #V18352
Attn: Diane Abramson
Must be US citizen or have Green Card
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