Analytics Engineer

• Perform statistical analysis to identify variances, trends, and correlations in the areas of member demographics, purchasing behaviors, product utilization, membership penetration and audience retention rates.
• Develop target audience models for membership acquisition and salvage campaigns based on data findings.
• Assist in the membership budget planning, forecasting and reporting process.
• Prepare narrative reports, charts, and illustrations that focus on key metrics such as member retention, attrition, promotion response, usage behaviors and trends.
• Analyze membership data on a daily, weekly, monthly, quarterly and annual basis to identify trends in new and renewal performance across all sales channels.
• Assess trends in membership renewal to reevaluate renewal program as needed.
• Compile and analyze direct mail results to measure effectiveness.
• Report findings, including recommendations, to senior leadership.
• Study data to identify areas of improvement for leadership decision-making; draw conclusions and make recommendations based on analysis from multiple data sources.
• Provide analytical support on a project basis to other business areas such as marketing to create and support membership acquisition and retention campaigns.
• Ensure metrics are accurate by analyzing data and processes for anomalies and or data/quality issues.
• Identify and resolve by coordinating with the appropriate business area regarding the source data.
• Develop, schedule and oversee delivery of daily, weekly, monthly, quarterly and annual results and deliverables to satisfy executive leadership membership report needs.
• Create and maintain process documentation, policies and procedures.
• Protect and strengthen the AAA brand.
• Perform other duties as assigned.

Membership Data Analytics Specialist

• Consult with teams across the organization to translate key product and business processes into technical data requirements. Use dbt, BigQuery, and SQL to build up Packback’s metrics layer to enable self-serve access to core analytics.
• Build, optimize, and orchestrate data pipelines with dbt, Airflow, and Python
• Establish data integrity standards and SLAs to ensure timely, accurate delivery of data
• Build insightful and reliable dashboards to track performance of core company metrics across the product and business
• Collaborate with business operations teams to define and train on best practices with respect to data modeling, analytics, and visualization
• Collaborate with leadership to conduct analyses and apply statistical methods to answer day-to-day questions or support larger initiatives
• Work within Packback’s research function with partner institutions and perform in-depth analyses to understand how Packback’s products are driving key student outcomes
• Consult on the adoption of new technologies that impact Packback’s data infrastructure

• Provides financial and regulatory reporting and analyses to maintain adequate controls over the financial and regulatory reporting processes
• Responsible for running complex business performance, risk and operational analytics
• Develops analytical methods/models to assess market, credit and/or operational risk of new and existing financial products
• Leverages business/product expertise to rigorously analyze large datasets, improve risk adjusted returns, deliver profitable growth, and communicate conclusions
• Synthesizes analytical results and develops, recommends, and implements business strategies that improve lending decisions, assist in managing risk, increase revenues, reduce exposure to losses, meet business goals, and improve performance
• Establishes baselines for strategies and tracks actual performance to expectations
• Applies predictive models, third party data, and other tools to develop and execute appropriate segmentation and targeting for acquisition and portfolio strategies to provide insight into portfolio risk
• Manages engagements with internal and external information suppliers ensuring solution is fit for purpose while maintaining appropriate governance and oversight
• Works with business, credit, data, and model development partners to design, develop, and monitor test designs and analytical reporting to track and enhance strategies
• Designs/enhances standard reporting suites for regular product/portfolio reviews
• Collaborates with the line of business, Finance, and Risk partners to assess and establish credit risk appetite and to understand its implications, as well as to establish policies and procedures governing the identification, monitoring, and management of risk appetite.

Portfolio Analytics & Strategy Specialist – Data, Modeling & Analytics

• Creates and leads the technical design and development of software solutions.
• Proposes & designs software solutions to address complex business needs.
• Prepares technical and procedural documentation required.
• Facilitates complex problem resolution.
• Provides technical guidance and support to colleagues.
• Reviews coding, testing, and documentation of software.
• Applies modern principles, methodologies and tools to advance business initiatives and capabilities.

Software Engineer Lead – ETL

• Design and develop data serving and semantic layers to support business needs ranging from traditional reporting to reverse ETL and LLM/AI implementations.
• Develop data models for use by analysts and applications from across the business using modern dimensional modeling practices to efficiently serve accurate, consistent data.
• Build and maintain robust, scalable data pipelines to extract, transform, and load (ETL, ELT) data from various sources into the data platform using both batch processing and event-driven patterns.
• Create efficient, performant data models to support business requirements and analytics needs.
• Implement and automate data quality checks and monitoring to ensure data accuracy and drive observability.
• Manage, troubleshoot and optimize existing data infrastructure, including cloud-based solutions and on-premises systems.
• Leverage cloud data platforms (Fabric, Databricks, Snowflake, etc.) for data storage, processing, and analysis.
• Work closely with data analysts, data scientists, and business stakeholders to understand their data needs and deliver solutions.
• Identify and resolve data-related issues and challenges for technical and non-technical stakeholders.
• Support company-wide projects ranging from server migrations to mergers and acquisitions as a data and systems expert.
• Automate data processes to improve efficiency and reduce manual effort.
• Implement modern concepts like metadata-driven pipelines and Infrastructure-as-Code that will play a key role in a scalable, resilient data platform.
• Document data processes, architecture, and workflows.

Analytics Engineer jobs in Ohio

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Membership Data Analytics Specialist

Analytics Engineer

Portfolio Analytics & Strategy Specialist – Data, Modeling & Analytics

Software Engineer Lead – ETL

Analytics Engineer