Unlock the Power of Data We live in a world where data-driven decisions are the norm, but what about the insights that remain hidden? Our technology connects communities of global smartphone users to source actionable data in real-time, cost-effectively, and with the visibility needed by leaders inside organizations to make informed decisions. This approach benefits both organizations and communities. Individuals can earn more from their opinions and discoveries, influence their cities for the better, and do it all with transparency as we value both data and the people providing it. Position Overview We're seeking an experienced Data Expert to play a key role in driving data excellence and analytical insights within our Market Performance Operations team. In this position, you will ensure the accuracy, consistency, and timely delivery of high-quality data, working closely with cross-functional teams to improve our processes and data products. Your efforts will directly impact the quality of our market research studies and contribute to data-driven decision-making across the organization. - Proven experience in managing data quality, data transformation, and data completeness processes. - Expertise with data pipelines, ETL processes, and integration tools like DataForm/DBTs, SQL, Python, etc. - Strong problem-solving skills with the ability to identify and resolve complex data issues. - Experience with standardizing data schemas, maintaining consistency across data sources, and using best practice techniques. - Knowledge of data automation and model development, particularly in large-scale environments. - Excellent collaboration skills, with the ability to work across cross-functional teams to drive results. - Develop and document a comprehensive Data Quality Management (DQM) process for commercial products, focusing on ensuring consistency, accuracy, and transparency across data operations. - Update the Data Governance approach, including the documentation of data governance rules and ownership. Clearly outline roles and responsibilities across teams to ensure adherence to data quality standards. - Establish a transparent ruleset for what data will be improved and what will not, providing clarity to all stakeholders on the scope of improvement efforts based on impact, feasibility, and business priorities. - Work with cross-functional teams to ensure alignment on the DQM process and its ongoing execution across the organization. - Define and track key Data Quality Metrics to evaluate and report on data quality performance. Establish targets for each metric and create systems for continuous monitoring and improvement. - Ensure stable, reliable, and accurate data production across all countries where MPS is active. - Lead efforts to improve data accuracy and reduce delivery timeframes across teams. - Develop and manage frameworks for measuring quality escapes and set reduction targets. - Ensure on-time delivery of high-quality market research studies. - Standardize and optimize quality processes to drive consistent results. - Collaborate with operations teams to implement strategies for continuously improving data quality. - Provide actionable recommendations for both short- and long-term improvements to data quality. - Develop and implement a framework to prioritize existing data quality alerts based on severity and impact. - Create a system to surface critical alerts that require proactive investigation and immediate resolution. - Collaborate with Customer Success, Data Delivery, and Operations teams to define key metrics for evaluating alert severity. - Drive continuous improvement in alert handling processes to ensure high-priority issues are addressed promptly. - Develop a framework to conduct root cause analysis to identify the underlying drivers of data quality issues. - Collaborate with cross-functional teams to pinpoint systemic issues and design solutions to prevent recurrence. - Develop and implement corrective actions based on insights from root cause analysis to improve data production processes. - Identify, understand, and resolve anomalies in data content, such as unexpected spikes in availability or changes in core census variables. - Develop predictive models to identify and manage anomalies proactively. - Drive the implementation of AQC check suggestions, collaborating with Product teams to integrate controls at data collection points. - Manage automated fraud detection models and ensure prompt identification of potential issues. - Propose and implement additional AQC checks based on identified data quality challenges. - Oversee segmentation and trend models, developing predictive tools to identify data anomalies and drive continuous improvements.