Technical Product Manager - Data

About this role

At Early Warning, we’ve powered and protected the U.S. financial system for over thirty years with cutting-edge solutions like Zelle®, Paze℠, and so much more. As a trusted name in payments, we partner with thousands of institutions to increase access to financial services and protect transactions for hundreds of millions of consumers and small businesses.

Positions located in Scottsdale, San Francisco, Chicago, or New York follow a hybrid work model to allow for a more collaborative working environment.

Candidates responding to this posting must independently possess the eligibility to work in the United States, for any employer, at the date of hire. This position is ineligible for employment Visa sponsorship.

Overall Purpose    The Technical Product Manager is a key role on our Data & AI team charged with developing the next generation of analytical technology for Early Warning Services. This role will focus on our data capabilities to improve both R&D and productionalization of predictive models.    The Technical Product Manager collaborates closely with Analytics, MLOps, Engineering team members and other business stakeholders to translate enterprise-wide stakeholder needs into technical model, data, reporting and analytics requirements, working across technology teams to facilitate the development of internal-facing data platforms, products or capabilities.    Essential Functions   • Define and deliver roadmap and technical requirements for data and analytics capabilities, processes, and tools to enable prioritized use cases across the enterprise. 

• Scope and prioritize activities based on business and user impact which defines product enhancements for both short-term and long-term. 

• Gain a deep understanding of end-user needs and experience (internal data consumers), identify and fill product gaps and generate new ideas that grow adoption and improve user experience. 

• Gather requirements for the Data Technology team on data processing and storage to facilitate a variety of model and analytics use cases such as effective analysis and reporting, data science exploration and model development, and data quality and anomaly detection. 

• Set and achieve success metrics to meaningfully improve business results, focusing on what success looks like for our internal data consumers and how accessible data and insights could help them deliver enterprise value. 

• Enforce data quality standards and processes and ensure that data governance policies, data lineage and metadata management are integral components of data product development. 

• Support the implementation, measurement, and activation of data-driven use cases. 

• Support the integration of strong data governance, risk, and security controls. 

• Support the company’s commitment to risk management and protect the integrity and confidentiality of systems and data. 

• Support the integration of MLOps workflows and data pipelines that enable model deployment and monitoring. 

• Participate in defining RAG and LLM-based product capabilities. 

• Ensure basic compliance with model governance, including lineage, metadata, model monitoring, and bias documentation. 

• Collaborate with AI and MLOps Engineers to support model deployment pipelines on AWS and on-prem technologies. 

    Minimum Qualifications   • Education and/or experience typically obtained through completion of a bachelor’s degree in STEM or related field. 

• 5+ years' experience or related experience in product management, data management, or consulting with a proven record of high performance, preferably with experience building data and analytics products. 

• 3+ years' experience with direct hands-on responsibility working with data or data teams (data engineers, data scientists, software developers, data analysts, etc.), business stakeholders and end-users. 

• Strong business intuition and the technical ability to understand, design, and explain complex product and data strategies to both business and technical audiences. 

• Proficiency with software development methodologies such as Agile and experience working with Scrum teams and working with Agile tools such as Jira. 

• Strong project and stakeholder management with the ability to work effectively with cross functional teams with diverse skill sets across all levels of the organization. 

• Excellent communications skills, both oral and written. 

• Hands-on experience writing, reviewing, and tuning SQL, Spark, and Python. 

• Comfort with product analytics and data visualization tools (e.g., Tableau). 

• Background and drug screen. 

  Preferred Qualifications   • Master’s degree in STEM or related field. 

• Deep understanding of foundational data and analytics concepts. 

• Proven track record of managing all aspects of a successful product throughout its lifecycle, with experience in launching brand new products. 

• Strong understanding of data management requirements in a regulated industry. 

• Experience in financial institutions, particularly payments, identity, and fraud analytics. 

• Experience working with terabyte size datasets. 

• Experience with change management and moving from on-prem to cloud. 

• Hands-on experience with Python or R, as a data scientist. 

• Understanding of data science tools and concepts and experience directly enabling data science teams or delivering data science use cases. 

• Experience with: AWS, Salesforce, SQL Server, Hive, Spark, SQL, and data architecture tools such as HDFS, Aerospike, ElasticSearch, Kafka, EKS. 

• Deep understanding of best practices and unique data and analytics requirements. 

Physical Requirements

Early Warning works together in a highly collaborative office environment.  As such, working conditions consist of a normal office environment. Work is primarily sedentary and requires extensive use of a computer and involves sitting for periods of approximately four hours. Work may require occasional standing, walking, kneeling an

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