Sr. Data Engineer
The Sr. Data Engineer will be 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 and external systems and to synthesize key findings which inform business, IT and executives of alignment on strategic strategies and opportunities.
-Support establishment an enterprise platform that will provide substantial customer information to the various business groups to help them make better business decisions.
-Consolidate the various platforms RCCL currently uses (Hyperion, Tableau, Microstrategy, Excel, Access, etc) into a unified environment in order to avoid maintaining multiple data warehouses (e.g. CMA, UIW, EDSS, etc) to supply important and timely information
- Increase the maturity of our current analytics capabilities by progressing from traditional BI to true Analytics in order to take advantage of the emerging technologies around Descriptive and Predictive Analytics.
-Support build out of our Data-As-A-Service environment to our business groups and Project Excalibur teammates in order to extract and leverage the data were seaming together via the Enterprise Data team. Inclusive of Supporting development build of our future-state Data Lake/Hadoop Environment.
-Synthesize data in many forms in an effort to discover the undiscovered on new service offerings, products, and customer findings
ESSENTIAL DUTIES AND RESPONSIBILITIES:
- Data scientists interprets and apply data in analyses, and explain findings to business audiences typically, to improve products and processes.
- 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 companyÂ¿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.
- 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 data 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
- Help with research related to customer based analytical practice and develop communications for management and strategies for building institutional knowledge Work with product and enterprise teams via both Agile And Waterfall Methodologies
- Masters degree in Statistics, Operations Research, Mathematics.
- 8+ years of experience
-Latest core techs skills: Cassandra, Kafka, Tableau, Microsoft Azure, AWS, AWS Redshift, Hadoop Hortonworks/Cloudera, Big Data. + Real Time data visualization web applications. Hyperion IR. Oracle Exadata is knowledge is a plus. SQL and PSQL.
Experience and expertise in multiple reporting platform
-Experience with customer analytics, modeling techniques such as regression, decision trees, data mining, neural networks, and clustering;
-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
-SQL knowledge is required
-Highly analytical, quantitative presentation skills and excellent strategic thinking and leadership skills are required.
-Expert level programming skills using SAS or similar, 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
-Cloud Graph Database Architectures and Deployments
-SAS, Oracle, SQL, Forecasting, Predictive response base modeling
-Cloud integrations and data movement
KNOWLEDGE AND SKILLS:
-Expertise in modeling, customer segmentation, analytical reporting, survey analysis, key drivers analysis, dashboards, etc
- Cassandra, Kafka, Tableau, Microsoft Azure, AWS, AWS Redshift, Hadoop Hortonworks/Cloudera, Big Data. + Real Time data visualization web applications. Hyperion IR. Oracle Exadata is knowledge is a plus. SQL and PSQL. Data Movement - ETL
-Have a proficient understanding of how to architect a clustered environment in order to process the variety, volume, and velocity of data that will be ingested