Director, Data Science – Customer Engineering

Our Company Changing the world through digital experiences is what Adobe's all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We're passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We're on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

The Opportunity We seek a senior, experienced 'hands-on' Data Science leader to join our Customer Engineering team within the Adobe Digital Experience (DX) Cloud Engineering. Customer Engineering (CE) focuses on multiple aspects of product experience for Adobe Experience Platform (AEP) and AEP-related Apps, including diagnostics and prevention of customer issues and technical enablement to help customers quickly and iteratively move through the product adoption lifecycle to realize business value. The CE team also partners closely with our Adobe Field teams (Pre-Sales, Consulting, and Support) Field and 3rd party partners to collect and synthesize real-world customer patterns to align our product roadmap and develop technical frameworks and tooling to help these field teams achieve scale and impact as they engage with customers.

As our AEP business grows, our product and broader engineering teams are challenged to scale themselves to meet the customer and field team demands. In particular, various teams need data-driven, actionable insights that help identify, prioritize, and focus people and technology investments to help customers struggling to run, operate, or grow business impact from their AEP E2E system. In addition, there is ample opportunity to infuse more customer self-serve intelligence into our products through reporting, analytics, and even AI assistance. This senior leader would be the founding member of a Customer Data Science (CDS) team to take on these challenges – requiring this leader to develop and execute a team charter and roadmap, resulting in new customer and operational KPI reporting, predictive intelligence (e.g., at-risk customers, customer maturity, etc.), and in-product customer usage and value frameworks in collaboration with other data science related teams, such as our ML ops and decision science platform teams.

What You'll Do

• Analyze large and complex data sets related to AEP customer platform health, usage, and performance metrics to uncover insights and identify opportunities to improve customer support processes, system implementation, or product enhancements
• Develop and monitor AEP key performance indicators (KPIs) and metrics to track customer-level E2E platform health, capability usage and adoption, value realization, and other critical customer platform success measures
• Conduct exploratory data analysis to identify patterns, trends, and correlations that can inform product and engineering strategy and guide decision-making
• Collaborate closely with product managers, engineers, and other cross-functional teams to understand customer <> product goals, translate business questions into analytical tasks, and provide data-driven recommendations
• Build statistical models and machine learning algorithms to predict customer issues, identify product adoption drivers (points of struggle), personalize product support interactions, and optimize product performance
• Communicate findings and insights effectively through clear data visualizations, reports, and presentations to technical and non-technical stakeholders
• Partner with engineering and other business intelligence teams to design and automate data pipelines, improve data tracking, data quality, and the overall data infrastructure supporting customer and platform analytics

What You Need to Succeed The optimal candidate will have 10+ years' experience in data science or related analytics roles (product, customer analytics), including a unique blend of applied data science technical expertise, analytical prowess, business savvy, communication skills, and leadership abilities to drive data-driven innovation and decision-making. Detailed list of desired skills as follows:

Technical skills

• Expertise in machine learning, predictive modeling, data mining, and advanced statistical techniques.
• Proficiency in programming languages like Python, SQL, and working with big data tools like Spark and Hadoop
• Experience with data visualization tools like Tableau for effectively communicating insights
• Knowledge of cloud platforms like Amazon Web Services for data processing and model deployment

Analytical and Problem-Solving Skills:

• Excellent analytical and problem-solving abilities to extract insights from complex datasets and drive data-driven decision-making.
• Curiosity and passion for exploring new techniques and staying updated with the latest advancements in data science
• Innovative mindset to develop novel solutions and find the "next big thing" that differentiates the organization

Business and Communication Skills

• Strong business acumen to understand organizational goals and translate them into analytical tasks.
• Ability to communicate complex technical concepts simply through data storytelling and visualizations.
• Consultative approach to collaborating with cross-functional teams and stakeholders

Leadership and Management Skills

• Leadership skills to guide and mentor junior data scientists and drive data science strategy.
• Project management experience to oversee end-to-end data science projects and initiatives.
• Ability to prioritize and manage multiple projects simultaneously while meeting deadlines.