Position Description:

**Applicants are permitted to work remotely from an at home work site in the United States**

Generates analytical insights to drive business actions using analytical tools and techniques (SQL, Qlik, Tableau, Python, and R) and big data technologies (Snowflake, Hadoop, and Hive). Improves product offerings using varied analytical techniques and myriad data sources — customer attributes and behaviors, transactional history, call transcripts, digital activity, and business financials. Brings a data-driven approach to decision making through experimental design and practical application. Informs business decisions and drives the actions of customer experience and product development teams using analytical insights.

Primary Responsibilities:

• Supports democratization of data among business partners and creates self-serve data visualization tools that enable business decision making.

• Improves data analytics and insights capabilities and spreads throughout the organization.

• Develops and drives strategic analytical initiatives.

• Formulates and applies statistical modeling and other optimizing methods to develop and interpret information that assists management with decision making, policy formulation, or other managerial functions.

• Proposes improvements on existing data modeling and processing for informed business stakeholder decisions.

• Collaborates with business partners to discuss problem areas with data measurement and quality control, and evaluate and implement corrective actions in data pipeline.

• Cross-functional strategic collaboration with multiple teams to develop standardization process for optimal program evaluation, review, or implementation.

• Ensure data model insights align with driving business objectives, gauge performance, identify areas for improvement, and provide recommendations for better decision making.

Education and Experience:

Bachelor’s degree (or foreign education equivalent) in Business Analytics, Project Management, Computer Science, Engineering, Engineering Management, Information Technology, Information Systems, or a closely related field and five (5) years of experience as a Senior Manager, Advanced Data Analytics and Insights (or closely related occupation) performing data analytics and insights in a large cross-channel enterprise environment.

Or, alternatively, Master’s degree (or foreign education equivalent) in Business Analytics, Project Management, Computer Science, Engineering, Engineering Management, Information Technology, Information Systems, or a closely related field and three (3) years of experience as a Senior Manager, Advanced Data Analytics and Insights (or closely related occupation) performing data analytics and insights in a large cross-channel enterprise environment.

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise (“DE”) writing advanced SQL in Web-based Cloud storage service environments — Amazon Web Services, SnowFlake, and Microsoft Azure; building data visualizations to answer strategic questions, extract actionable insights, build datasets for ad hoc, and recurring analysis, using Tableau; preparing data to empower end users and evaluating data availability and usability for current marketing metadata, customer, and transaction data, using data sources — marketing campaign metadata, customer profile data, customer interaction data, and transaction data; and enhancing data quality and interpretability using data-flow diagram.

• DE driving the strategy and adoption of analytic products, and providing thought leadership on translating complex business needs into efficient analytical plans in an agile work environment; extracting analytic insights to drive strategy for marketing, experimentation, campaign measurement, customer segmentation, customer acquisition, and engagement domains, using R, Python, Adobe Analytics, Tableau, PowerBI, and Microsoft Excel; and testing business hypothesis to assist decision-making using statistical methods in R or Python.

• DE formulating, validating, testing, and applying Machine Learning (ML) methods to predict customer activities, optimize marketing strategies, and assist management with decision making and policy formulation, using statistical and ML packages (Xgboost, randomForest, Scikit-Learn, and SciPy), and functions in R and Python; performing technical architectural development and implement process flow to enhance customer experience through near real time automation.

• DE crafting data architectural solutions, developing user requirement, mapping data flows and collaborating with enterprise architects and software engineers to deliver platform architectural solutions for multiple use cases and projects.

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