Senior Data Product Manager

Allergan Data Labs is on a mission to transform the Allergan Aesthetics beauty business at AbbVie, one of the largest pharmaceutical companies in the world. Our iconic brands include BOTOX® Cosmetic, CoolSculpting®, JUVÉDERM® and more. The medical aesthetics business is ripe for rapid growth and disruption, and we are looking to add to our high performing team to do just that. 

Our team has successfully launched a new and innovative technology platform, Allē, which serves millions of consumers, tens of thousands of aesthetics providers and thousands of colleagues throughout the US. Since its launch in November 2020, Allē has delivered curated promotions, personalized experiences and had millions of consumers use it as part of their beauty journey. 

We’re looking to add to our team as we prepare to launch a new array of game-changing technologies on our successfully adopted platform. If you’re interested in working within a startup-oriented environment, while having the backing of a very large company, please read on.

Allergan Data Labs is a vibrant startup-minded organization with the backing of a large company. Allergan Data Labs uses data to deliver insights and build data-driven solutions for products, operations, marketing, and sales. As a Senior Product Manager reporting to the Head of Data, you will be responsible for collaborating with cross functional partners, coordinating with data teams, and applying your data & product knowledge to conceive, design, and shepherd data products through deployment. Our data products include curated datasets built by data engineers, augmented data elements developed by data scientists, as well as machine learning (ML) and AI solutions accessible through a variety of interfaces such as microservice APIs.

Responsibilities

• Manage a portfolio of data products consisting of curated datasets and AI/ML solutions accessible through a variety of interfaces

• Research, conceive, and document new data products through user interviews, surveys, and concept testing

• Work with partners (Product Engineering, Marketing, Sales, Operations, BI, etc.) to document requirements for data products including objectives, performance, and ROI

• Coordinate with software Product Managers to ensure that data products are accessible to end users through interfaces or integration into software products

• Prioritize development of data products based on user feedback, technical feasibility, resources, strategic goals, and ROI

• Work with Data Technical Project Managers to set development schedules, report status, and deliver products on time

• Collaborate closely with Data Science & Engineering teams to ensure seamless integration of data products within our data ecosystem

• Coordinate A/B testing and other approaches to quantify the performance of data products

• Define & report KPIs to measure data product performance, user adoption, and ROI

• Ensure that all data governance best practices are utilized, including data classification, privacy controls, performance & lineage observability, and inclusion in the data catalog

• Work with the Head of Product and Head of Data to define a data product strategy that aligns with business objectives, internal capabilities, and market opportunities

• Clearly present data products & informational materials at the appropriate level of detail to executives & business partners

• Maintain sharp professional knowledge & skills, and stay abreast of new developments in data technologies, data science, ML, and AI

• Mentor and supervise less senior staff

Required Experience & Skills

• BS or MS degree

• At least 3 years as a Product Manager having launched multiple software or data products

• At least 2 years of experience in defining, building, and deploying data products in particular

• Skilled at identifying new products, performing product discovery, user interviews, surveys, concept testing, and A/B testing

• Because this role will benefit from technical knowledge to guide the management of data products:

  • At least 2 years of prior experience as an individual contributor in data-related roles such as data engineer, data scientist, data analyst, or data-centric software

  • Broad understanding of basic approaches to models and algorithms for ML, AI, and data analytics

  • Experience with data storage architectures such as relational databases, data warehouses, data lakes, lakehouses, and data mesh

  • Basic