AI Native, Strategic Analytics Manager

ConsumerAffairs

About The Position

The Strategic Analytics Manager will play a critical role in enabling data-driven product innovation and AI advancement at ConsumerAffairs. This role partners closely with Product to build scalable data solutions that empower teams to answer questions independently while providing deeper strategic analysis on complex business challenges. It blends product analytics, experimentation strategy, AI enablement, and advanced modeling to support both our consumer experiences and AI-driven SaaS initiatives. This role is responsible for designing and maintaining the data foundations that power experimentation, product optimization, and AI-enabled decision systems. Key initiatives include supporting A/B testing strategy, improving conversion performance across paid and organic channels, building pricing and growth models, and ensuring classification and AI-assisted workflows operate with reliable, deterministic behavior where required. Deliverables include scalable dashboards and self-serve tools, deep analytical modeling, experimentation design support, and translating complex findings into clear, actionable narratives for product and executive leadership. The successful candidate will demonstrate systems-level thinking, intellectual curiosity, and a passion for building sustainable data infrastructure that scales. They will excel at structuring ambiguous questions, applying AI responsibly, and converting analytical insight into durable product improvements. These responsibilities are not to be construed as a complete statement of all duties performed. Employees will be required to perform other job-related duties as required

Requirements

Bachelor’s degree in Business, Economics, Statistics, Data Science, or a related field.
3-5 years of experience in data analysis, business intelligence, or a related role.
Advanced proficiency in SQL required; strong Python skills preferred for modeling, experimentation analysis, and automation.
Experience with data visualization tools (e.g., Tableau, Power BI) and building scalable, self-serve analytics solutions.
Strong understanding of data warehouse architecture and data modeling principles.
Experience supporting experimentation frameworks (A/B testing, conversion analysis, performance measurement).
Familiarity with classification models, predictive modeling, or AI-assisted analytical workflows.
Working knowledge of Large Language Models (LLMs), GPT-based systems, and practical applications of AI in business environments.
Ability to design analytical systems that produce reliable, consistent, and deterministic outputs where required.
Demonstrated ability to take initiative, think systemically, and translate complex data into clear, actionable insights.
Must be highly curious, driven, and disciplined
Excellent communication and people skills
Obsessed with ensuring an exceptional customer experience- for both internal and external customers.
Stands up for decisions, takes responsibility for results, and shares both good and bad outcomes transparently.
Demonstrates a relentless focus on results with a commitment to deliver;
Takes decisive action, and confidently changes course if unsuccessful.
Displays a growth mindset to continually improve; encourages everyone around them to be tenacious and never settle.
Constantly seeks feedback to improve; Focuses on solving issues through teamwork, and collaboration
Acts with urgency; delivers top results in hours and days instead of weeks and months.
Relentless in their pursuit of success and possessing the willpower to embrace challenges as opportunities.

Nice To Haves

Industry experience is beneficial

Responsibilities

Analyze large and complex data sets to identify trends, patterns, and insights that drive product strategy, experimentation, and AI-enabled decision-making.
Design and build scalable dashboards, data models, and self-serve tools that empower Product and cross-functional teams to independently answer key business questions.
Partner closely with Product Managers to support A/B testing, conversion optimization, SEO performance, and matching tool enhancements .
Develop and validate analytical and classification models, ensuring reliable and deterministic behavior where required for production decision systems.
Translate ambiguous business questions into structured analytical frameworks and AI-assisted workflows.
Present findings and strategic recommendations to senior leadership in a clear, actionable, and decision-oriented manner.
Monitor performance of experiments, product initiatives, and AI-driven systems, recommending iterative improvements based on data.
Stay current with emerging analytics and AI technologies, proactively identifying opportunities to responsibly scale AI capabilities across the organization.