Senior Manager, Analytics and Data Science - Firefly

The Opportunity: 

Adobe Firefly is transforming how creators ideate, create, and express themselves through generative AI. As Firefly continues to scale, data-driven growth and high-quality experimentation are core to how we learn, prioritize, and deliver value to millions of users. 

This hybrid role mixes hands-on analytical tasks with strategic leadership as you build and expand a team during rapid growth. You will work closely with Firefly Product, Leadership, PMM, GTM, PLG, and Engineering teams. You will also collaborate with participants across the organization to influence strategy, roadmap, and investment decisions throughout the customer lifecycle. Your duties include developing insights that guide product and business choices and creating data science models. 

If you are passionate about AI and creativity, data-driven decision-making, systems, and design thinking, and thrive in a dynamic environment, we encourage you to apply. Join our team to shape the future of digital creativity with Adobe's generative AI. This opportunity lets you reach millions of creatives and help them change how they work.  

What you’ll do: 

• Play a hands-on analytical role during your first few months. Then, transition to managing, mentoring, and leading a team of data analysts and scientists. You will ensure high-quality work, clear growth paths for team members, and balanced resourcing across workstreams. 

• Develop and maintain a deep understanding of our customers, products, and business performance to inform data-driven decisions 

• Function as a trusted advisor for counterparts on Product, Marketing, GTM, PLG, and Engineering teams to guide the roadmap by providing data-driven insights and proposals 

• Partner with senior and executive leadership to shape Firefly's analytics and experimentation strategy 

• Anticipate risks and roadblocks before they surface, and proactively define and prioritize the opportunities most worth pursuing to grow the business 

• Define important measurements and lead monitoring of these to assess product performance and track product health 

• Partner with multi-functional partners and the analytics product manager to develop and complete a roadmap of analytics initiatives. These initiatives will drive the most business value for the suite of Firefly products the team manages. 

• Perform advanced deep dives, build predictive models and dashboards to mine insights 

• Combine data, experimentation, and insights based on detailed examination to deliver actionable recommendations that address opportunities for product improvements  

• Improve reporting and data tools to empower data-driven decision-making in the workstreams you support 

What you’ll need to succeed: 

Required: 

• BS, MS, or PhD in an analytical field: statistics, applied mathematics, computer science, engineering, economics, physics etc. or equivalent practical experience 

• Over 4 years of experience leading analytics & data science groups, including mentoring senior individual contributors 

• 5+ years of proficiency in Python and SQL 

• Strong proficiency in querying and manipulating large datasets using SQL-like languages on cloud (Databricks, Spark-SQL, Airflow) 

• Strong fundamentals in statistics as well as shown skills in data visualizations 

• Experience with A/B testing and sampling methods 

• Good communication and relationship building skills 

Preferred / nice-to-have: 

• A track record spanning over 3 years in contemporary data science processes in cloud environments (Git, Jupyter, Python, AWS, Azure)  

• Ability to support multiple ongoing projects in a fast-paced environment 

• Solid background in data warehousing, data modeling, data access, and data storage techniques 

• Experience crafting dashboards in Tableau or PowerBI 

• Expert in one or more data science tools such as Pandas, NumPy etc 

• Experience with Adobe Analytics or a similar web analytics tool 

• Experience building data processing machine learning models in a product environment 

• Familiarity with ML for propensity estimation and causal inference with observational data or experimental designs 

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