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Job Description

• Build a Community of Practice (CoP) and provide constructive feedback with this team that are the Subject Matter Experts (SMEs) in their content and data science areas. Evolve this CoP with the Data Driven Excellence CXL operating under the strategy and business operations.
• Responsible to work with Content QA Team & Analytics QA Team so that it offers best-in-class operations across channels.
• Maintaining quality standard process & aiming for Optimization of content QA processes (covering Content Review, Content Proofing, functionality, responsiveness, Readability & Design consistency).
• Continuous Improvement of the Quality processes by researching, understanding and implementing the various Automation Tools for QA/QC such as TextVerify, BrowserStack Percy etc. to reduce errors and exacting timelines.
• Ensure that E2E Audit process is robust such that any asset that is expired is not only removed from channel that it was delivered on but also decommissioned with accompanyingrules/configs/workflowsin the respective channels.
• Responsible to make sure that the vendor teams perform QA of all VAEs & IDAs includingtesting e-mails, links, token functionalities and CTAs,
• Content alignments, renderings & HTML Build using Knak,Package handover, CV & RV handover, Logging issues and assigning to form team.
• Quality Checking the IDA navigations, animations, thumb images, slide loading, & flickering issue.
• Pinch and Zoom function, superscript link and checks.
• Responsible to work with Web, Reporting and Analytics teams to analyze Root Cause Analysis - (campaign or platform related) when issues/defects are raised.
• Instills a culture of continuous improvement, testing, and deployment of new capabilities for the business and build a channel of practice to promote the knowledge across delivery teams.
• Responsible to implement automation tools in the delivery space to provide feedback with operational issues in BAU processes. Rephrased this responsibility.
• Understand data at a macro level of campaign E2E so that you can demonstrate a high level of understanding of the data points across integrations in the MarTech Stack of OBU & BBU when E2E Validation/audits is performed.
• Capability in applying deeper technical skills and knowledge that is shared across the functional area (e.g., deep knowledge of key data sets, modeling capabilities, etc.)
• As the Data Assurance lead, you will lead automations and processes that ensure quality data is provided through End to End pipelines in the MarTech systems.
• Be a Liaison with the Data CXLs through your team within GCO so that the capabilities received from IT are liasoned with GCO Data Channel Excellence Lead.

• 6+ years of Data exp. in Data Warehousing/Mining.
• RDBMS Systems like Oracle, MySQL, Microsoft SQL Server, PostgreSQL, SQLite, Teradata, or non-relational document database like MongoDB.
• Solid understanding of Databases, DM schemas and SQL.
• Designing or understanding the architecture/road map of new data or content capabilities.
• Act as a consultant when needed for supporting GCO Omnichannel Teams with insights and solutions for data related projects.
• 1-2 years of exp. in development using Power BI tool(MicroStrategy/MicrosoftPower BI).
• Knowledge of Big Data Applications, understanding its flow & architecture.
• A quantitative bachelor's degree from an accredited college or university is required in one of the following or related fields: Engineering, Operations Research, Management Science, Economics, Statistics, Applied Math, Computer Science or Data Science. An advanced degree is preferred (Masters, MBA, or PhD).

• Experience in the pharmaceutical industry with data warehousing is a plus.
• Experience of leading the technical delivery of large scalable Omnichannel solutions preferable.
• 2+ years of experience in Pharmaceutical / Biotech / Healthcare analytics or secondary data analysis.
• 3+ years of experience in application of advanced methods and statistical procedures on large and disparate datasets, specifically:
• Statistical Analysis & Modelling: Design of Experiments, Time Series, Regression, Applied Econometrics and Bayesian methods.
• Statistical analysis and modelling background with Data Mining, Predictive Modelling & Machine Learning algorithms is a plus.
• Working knowledge of data visualization MicroStrategy, Tableau, PowerBI, QlikView, D3js or similar tools.
• Optimization & Simulation of data and ability to use tools like Tealium Predict/ Tealium Data Insights is a plus.
• 2+ years of recent exp. and proficiency with Python, R, SQL, and big data technology - Hadoop ecosystem (Cloudera distribution - Impala, Hive, Hbase, Spark, MapReduce etc.). Background with Machine Learning/AI is a plus.

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