Simplifying data enablement workflows; liaising with data-producing teams at Bloomberg to onboard data for AI and make relevant metadata discoverable.
Streamlining data access patterns throughout the entire machine learning lifecycle, from exploratory data science and analytics to large-scale training, to feedback pipelines at model serving time.
Expanding our infrastructure portfolio with data quality, enrichment, and other data value-add needs to make a cohesive experience when curating AI-ready data.
Partner closely with AI product teams to accelerate their critical machine learning projects, with a preliminary focus on data enablement initiatives for generative AI
Interact with our machine learning and data science experts, interview them to understand their workflows and technical requirements, develop a deep understanding of their data needs
Develop a roadmap, design patterns, and tools needed to empower, operationalize, and automate data delivery
Foster a culture of collaboration with your Engineering counterparts
Prioritize, plan, make decisions, ask the right questions, and understand how to manage resources effectively
Develop a long-term technical strategy, roadmap, framework, guard rails, design patterns, and tools for improving data access to support ML workflows
Do the right thing; be part of a Product team and CTO organization that optimizes for the long-term
Requirements & Skills:
5 + years of experience in a Product Management role
Experience working with data teams and automating ML and other data-intensive application development workflows
Deep understanding of identity and access management
Organizational and communication skills to effectively coordinate and work with engineers, other product managers, and senior management
A product-driven focus and track record of shaping business strategy and roadmaps for technical products
A degree in Computer Science, Engineering, Data Science, a similar field of study, or equivalent work experience
Nice to have:
Experience with public cloud providers such as AWS, GCP, or Azure, or cloud-based machine learning platforms
Proven data literacy, understanding of data lineage, and provenance
The breadth of knowledge around data streaming, storage, cataloging, and retrieval technologies such as S3, HDFS, Hadoop, HBase, Hive, Trino, Presto, Cassandra, Spark, Flink, Kafka
Prior experience as a technical product manager or engineering technical lead
