Job Title Omnichannel Data Assurance & Content QA Lead About the role Manage a team comprising of Data Assurance QAs & Content QAs (managing Print & iPDFs, Omnichannel Assets) within AZ and Indegene to deliver Quality Omnichannel Campaigns within prescribed SLAs (Service Level Agreements) in the QCoE (Quality Center of Excellence) tower. 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 (Channel Excellence Lead) 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 accompanying rules/configs/workflows in the respective channels. Responsible to make sure that the Indegene vendor teams perform QA of all VAEs & IDAs including testing 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. Develop a deep understanding of internal customers’ data across all the systems and understand data gaps in Campaigns that cause data quality issues. Responsible to work with Web, Reporting and Analytics teams to analyze Root Cause Analysis (RCAs) – (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 (Business as Usual) 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 (Oncology Business Unit) & BBU (Bio-Pharma Business Unit) 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 (Marketing Technology) 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.
Liaison with the POD QA Leads to make sure that incidents that have been routed to the Pool Specialists (Pool – this looks like a typo, I am not sure) are handled within the Incident SLAs. Present relevant Metrics and Team Utilization & Key highlights in PMO Governance meeting. Essential Skills and experience 6 years of Data experience in Data Warehousing/Mining. in RDBMS (relational database management system) Systems like Oracle, MySQL, Microsoft SQL Server, PostgreSQL, SQLite, Teradata, or non-relational document database like MongoDB. Drive Innovative solution to standardize/optimize an existing Campaign process/operations Recommending solutions to the team/customers for sophisticated reporting tasks. Solid understanding of Databases, DM (Data Management) schemas and SQL. High Level understanding of Content Delivery in Marketing paradigm.
Designing or understanding the architecture/road map of new data or content capabilities. Experience in gathering Data Requirements to demonstrate Full life cycle implementation experience using various SDLC (System Development Life Cycle) methodologies. Act as a consultant when needed for supporting GCO (Global Commercial Operations) Omnichannel Teams with insights and solutions for data related projects. 1-2 years of experience in development using Power BI (Business Intelligence) tool (MicroStrategy/Microsoft Power BI). Knowledge of Big Data Applications, understanding its flow & architecture. Act in the proficiency as Data Scientist to understand, manipulate and extract insights from large longitudinal commercial data sources of HCP/Patient level data sets.
Solid understanding in Databases and Complex SQL with ability to understand data flow across ETLs (Extract, Transform, and Load) and Snap logic Pipelines. 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 MS Office products – Excel and PowerPoint skills required. Expertise in managing and analyzing a range of large, secondary transactional databases is required. Experience with data visualization methods and tools Ability to derive, summarize and communicate insights from analysis and arrive at Root Causes of issues.
Organization and time management skills Desirable Skills and experience 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 experience 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. A good knowledge of ETLs like Informatica will be an added advantage to understand data through pipelines. Experience in providing Customer (Marketing Teams/Brands) Satisfaction and ability to engage, build and maintain credibility with Commercial Leadership Team. Experience using Big Data is a plus. Exposure to SPARK is desirable Strong leadership and interpersonal skills with demonstrated ability to work with many business leaders and multi-functional business partners.
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