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Lead Data Scientist - Marketing

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Responsible for analytical support and statistical modeling for the purpose of maximizing revenue. Accountable for driving valuable fact-based and quantitative consumer insights from internal systems and to synthesize key findings which inform business and strategic marketing strategies.

Responsibilities:
-Data scientists interprets and apply data in analyses, and explain findings to business audiences typically, to improve products and processes.
-Projects support business decision making for multiple business functions.
-Develops and executes statistical and mathematical predictive model solutions to business problems.
-Frames problems then determines intended approach and quantitative methods to develop solution.
-Uses analytical rigor and statistical methods to analyze large amounts of data, culling actionable insights using advanced statistical techniques such as predictive statistical models, customer profiling, segmentation analysis, survey design and analysis and data mining.
-Develops new algorithms and mathematical approach to understand the company’s audiences and solves complex business problems such as optimizing product performance, revenue and adoption.
-Researches new ways for modeling and predicting end-user behavior.
-Designs experiments to answer targeted questions.
-Documents projects including business objective, data gathering and processing, leading approaches, final algorithm, detailed set of results and analytical metrics.
-Develops materials to explain project findings
-Works with marketing business units on special projects relating to formulating data driven solutions and analyzing core marketing data involving business activity.
-Assist management in promoting and developing a strong sense of analytics culture based on data facts, teamwork and contribution
-Support the production of customer predictive models (Decision tree, Linear / Logistic Multivariate Regression Modeling), analytical studies, and deliver accurate customer based insights on spending behavior, response modeling, customer scoring, forecasting, customer lifetime value, and other data sources compiled from multiple tools and sources.
-Ensure valuable model insights are evaluated for long-term reporting utilization. Build / Rebuild predictive models / segmentations supporting direct marketing
-Track effectiveness of marketing models, incremental sales and ROI per selection, interpret data models and provide insights to management.
-Assess relationships for sales KPIs and suggest promotions based on customer behavior
-Performs duties by collecting data, analysis, and makes recommendations to management relevant to the strategic direction of marketing programs.
-Analyzes market conditions, sales trends, customer preferences and competitive behavior
-Drive and ensure continued definition, evaluation and analytical review of campaign success metrics and customer segmentations
-Develop strategies for prioritization of analytical project initiatives through supportable analytical projects which identify greatest and most immediate financial impact or enhance customer experience
-Help with research related to customer based analytical practice and develop communications for management and strategies for building institutional knowledge

Requirements:
-Master’s degree in Statistics, Operations Research, Mathematics.
-Experience in related field; Required 8 years
-Experience with customer analytics, modeling techniques such as regression, decision trees, data mining, neural networks, and clustering; Required 5-7 years
-Knowledge of database marketing experience across online and offline marketing, including integrated marketing measurement techniques.
-Experience in a large corporation or consulting firm practicing marketing strategies, modeling, CRM and management sciences/statistics is; Highly desired.
-Experience with data mining (S.E.M.M.A), data preparation, consolidation, imputation, transformation, interaction, variable reduction, linear and logistic multivariate regression modeling, decision tree modeling, post mortems, and manipulating data and modeling using SAS Enterprise Guide and Enterprise Miner.
-SQL knowledge is required.
-MS office products, Teradata knowledge is a plus.
-Highly analytical, quantitative presentation skills and excellent strategic thinking and leadership skills are required.
-Expert level programming skills using SAS as a programming language to meet the challenges of advanced data manipulation, complicated programming logic, and large data volumes is required.
-Experience of SAS programming using SAS/BASE, SAS/MACRO, SAS/SQL, SAS/STAT, and SAS/GRAPH, SAS Stored Processes in a data intense environment
-Experience with SAS Enterprise Guide, SAS Enterprise Miner is required.
-Experience with SAS Marketing Automation, SAS Data Integration Studio, SAS Web Report Studio, SAS OLAP
-SAS Information Map Studio is preferred.
-SAS, Teradata, SQL, Forecasting, Predictive response base modeling

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