What are the responsibilities and job description for the Sr Adobe Customer Journey Analyst position at Golden Technology?
About the Role
As a Senior Analyst focused on AI-Enabled Shopping, you will play a pivotal role in shaping the future of agentic commerce. This position combines advanced analytics, cross-functional collaboration, and strategic storytelling to accelerate the delivery and optimization of AI-powered shopping experiences.
You will leverage data from multiple sources to identify trends, uncover actionable insights, and make recommendations that enhance how AI shopping agents engage with customers. By partnering closely with product, engineering, and data science teams, you will define measurement frameworks, enable effective reporting, and ensure that agentic experiences are measurable, optimized, and continuously improving.
Experience & Background
- 3 years of experience using analytics tools such as Adobe Analytics (CJA), Power BI, SQL, Tableau, or similar platforms. Adobe CJA experience required.
- Intermediate experience executing statistical methods and correlation analyses that demonstrate business-relevant results.
- Experience innovating and building new analytics capabilities that enable insights to be delivered better, faster, and more cost-effectively.
- Experience with commercial behavioral data, e-commerce analytics, navigation/path analysis, search, and testing methodologies.
- Intermediate storytelling skills to engage stakeholders and empower faster, more confident decision-making.
- Knowledge of data wrangling, cleaning, and transformation techniques for large, complex datasets.
- Strong analytical mindset with ability to derive actionable insights from data.
- Experience working with recommendation systems, search algorithms, or conversational AI platforms (preferred).
- Understanding of machine learning concepts and familiarity with AI development lifecycle.
- Familiarity or experience with LLMs, SLMs, and generative AI models.
- Understanding of ecommerce metrics, customer acquisition funnels, and retail business models.
- Excellent written and verbal communication skills with ability to influence stakeholders at all levels.
- Strong customer empathy with ability to translate user needs into technical requirements.
Mindset & Approach
- Entrepreneurial spirit with comfort operating in ambiguous, fast-moving environments.
- Curious and proactive approach to seeking inputs, aligning on goals and delivering insights.
- Systems-thinking approach to problem-solving with attention to both user experience and business outcomes.
- Passion for emerging technologies and their potential to improve customer experiences.
Key Responsibilities
- Performance Tracking & KPI Strategy
- Monitor and analyze KPIs and North Star metrics for AI-powered shopping experiences to assess effectiveness, identify trends, and recommend opportunity areas.
- Experimentation & Continuous Improvement
- Contribute to the design, implementation, and evaluation of A/B tests for prompts, engagement strategies, and experience variations to enhance agentic commerce performance.
- Insights Development & Reporting
- Build and maintain custom dashboards and reports that consolidate multiple data sources, track longitudinal trends, and provide actionable insights for ongoing optimization.
- Anomaly Detection & Root Cause Analysis
- Detect and investigate anomalies in performance data, recommending mitigations and corrective actions to maintain product and metrics health.
- Cross-Functional Collaboration
- Partner with product, engineering, and data science teams to translate insights into product enhancements and operational improvements.
- Advanced Analytics & Tools Management
- Manage and act as a key advisor on analytics platforms (e.g., Adobe Analytics, Power BI) to perform end-to-end analyses, identify key drivers of emerging trends, and deliver actionable recommendations
- Measurement Framework Leadership
- Provide guidance on success measures, KPI strategy, and measurement frameworks across product teams to enable effective reporting and decision-making.
- Data Storytelling & Stakeholder Engagement
- Present insights through compelling narratives that align supporting data to substantiate recommendations, driving usability and effectiveness of AI-enabled shopping experiences.