Responsibilities

• As a Business Intelligence and Marketing Analyst, you will be responsible for delivering insights and recommendations related to the marketing of AAA Life’s various products.
• You will partner with marketing staff, marketing data managers, and other data analysts and data scientists to identify business questions, gather data, perform appropriate analyses, and deliver insights and recommendations.
• This role requires proficiency in SQL, R or Python, a visualization tool such as Power BI or Tableau, and a passion for delivering actionable insights and driving the growth of the organization.
• Design, build, and automate user friendly PowerBI dashboards to enable data-driven decision making by our stakeholders, including:
• Developing data quality frameworks
• Creating standardized reporting templates
• Conducting advanced customer segmentation analyses
• Conducting advanced modeling decile analyses
• Supporting strategic planning with actionable data-driven insights
• Track marketing initiatives, produce 360-degree campaign results analysis, validating against forecast and plan, proactively identifying actionable opportunities for results improvement, providing status reports and strategic recommendations to business stakeholders. Specifically, focus on:
• Increasing dashboard efficiency
• Increasing insight impact
• Process automation success rates
• Shortened time to deliver actionable insights
• Collaborate with marketing stakeholders to identify business questions and challenges, then perform appropriate analyses and deliver actionable insights and recommendations.
• Work with marketing data team and service providers to ensure data is complete, correct, and suitable for analysis.
• Design and conduct hypothesis testing (A/B testing and multi-variate testing) to evaluate the effectiveness marketing activities or strategies
• Maintain clean and organized documentation of data, methodologies, and results in a central depository.
• Identify opportunities for automation in existing processes to improve overall efficiency. Recommend new processes to enhance efficiency and performance.
• Back up data scientists and modelers whenever business requires. Comfortable with building statistical models, using ML/AI platforms and algorithms, and marketing technology.

Requirements

• Possess strong analytical and problem-solving skills. Able to effectively communicate complex analytical findings in a candid, clear, and concise way with both technical and non-technical audiences. Able to present findings persuasively.
• Can maintain perspective between the big picture and the tactical details. Remains aligned with the organization’s strategic plan
• Capable of maintaining solid working relationships with other people. Works well as part of a team
• Stellar attention to detail, including maintaining accuracy and consistency across a suite of analytics assets, keeping documentation up to date, and proactively identifying and addressing any quality concerns.
• Self-starter with the ability to identify priorities and focus on items with high business impact
• Demonstrated ability to translate business requirements into automated reporting solutions. Understanding of marketing metrics and KPIs with focus on automated tracking. Proven track record of implementing report automation and self-service analytics

Preferred

• Master’s degree in Statistics, Mathematics, Data Science, Business Analytics, or related field
• Bachelor’s degree in Statistics, Mathematics, Economics, Data Science, Business Analytics, or related field
• 5+ years of experience in business analytics
• Proficiency in SQL, Python or R, and visualization tools such as Power BI.
• Proficiency in cloud platforms (AWS, Azure, Google Cloud)
• Understanding Machine Learning frameworks
• Proficiency in version control systems (Git)
• Experienced with cloud platforms such as AWS, Azure, and Google Cloud. Familiar with big data technologies (Spark, Hadoop)
• In-depth experience with hypothesis testing, including test design and analysis in marketing, including both digital marketing and direct mail.
• Advanced training or academic focus in non-parametric statistics, resampling methods, or Bayesian approaches for small sample inference
• Experience applying sequential testing or multi-armed bandit approaches to maximize insights from limited samples in marketing contexts
• Experience with data visualization best practices and automated dashboard design.
• Experience with compliance and Data Governance
• Data privacy compliance (GDPR, CCPA)
• Ethical data handling practices
• Data security best practices