Sr. Lead Data Product Manager

Early Warning® • Scottsdale, AZ

1d • $180,000 - $240,000 • Hybrid

About The Position

The Sr. Data Product Manager is a strategic role within the Certos Data & Analytics organization focused on enabling Data Science and Analytics teams through deep data management expertise. This leader drives the vision and requirements to scale and improve second- and third-party data, with an emphasis on quality, usability, and risk management. By translating stakeholder needs into actionable data, reporting, and analytics requirements, the role partners closely with data science, analytics, and technology teams to deliver high-quality, trusted data products that accelerate model development, insights generation, and compliant data use. This role will be critical in enabling our future state data science and ML Ops platform and support the requirements to build out capabilities. The Sr. Lead Data Product Manager serves as the dedicated Data Product Manager for the Data Science organization, partnering closely with Data Scientists, Data Engineers, and ML Ops teams to enable adoption of the enterprise data and machine learning platform (Domino Data Lab). This role will dive deeply into customer pain points, technology and security constraints, and market trends to develop a vision and requirements to scale second- and third-party data focusing on quality, usability, and risk management. They will translate stakeholder (internal/external) needs into technical data, reporting and analytics requirements, and partner across technology teams to facilitate the development of data products and capabilities.

Requirements

• Bachelor’s degree in STEM or related field
• 9+ 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
• 5+ 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 and tuning SQL
• Comfort with product analytics and data visualization tools (e.g. Tableau and Mixpanel)
• Background and drug screen

Nice To Haves

• Master’s degree in STEM or related field
• Experience supporting Data Science, Machine Learning, or Advanced Analytics teams through platform modernization, cloud transformation, or ML Ops implementation initiatives.
• Strong data management background, including hands-on experience with data sourcing, data lineage, metadata, data quality, and data governance concepts.
• Demonstrated ability to analyze data issues, write complex queries, and work directly with engineering teams to troubleshoot data pipelines, integrations, and platform-related challenges.
• Experience managing product backlogs that balance business value, technical debt, operational risk, platform stability, and regulatory requirements.
• Familiarity with modern data science and ML Ops platforms such as Domino Data Lab, Databricks, SageMaker, or similar environments.
• Working knowledge of model development lifecycle, feature engineering, model deployment, and ML governance processes.
• Experience working with terabyte size datasets
• Understanding of data science tools and concepts and experience directly enabling data science teams or delivering data science use cases
• Experience with: Salesforce, Google Analytics, SQL Server, Hive, Spark, SQL, and data architecture tools such as HDFS, Aerospike, ElasticSearch, Kafka
• Deep understanding of best practices and unique data and analytics requirements across functional areas such Product, Marketing, Data Science, Finance, Operations

Responsibilities

• Articulate vision, roadmap and technical requirements for data and analytics capabilities, processes and tools to enable prioritized use cases across the enterprise or business unit
• Act as the primary liaison between Data Science and ML Ops teams, translating business and technical requirements into actionable platform capabilities, migration plans, and backlog priorities.
• Lead requirements gathering, prioritization, and execution planning for the migration of data science workloads, models, and analytical processes to the enterprise ML Ops workbench.
• Manage and prioritize a balanced product backlog that includes new features, technical debt, operational risks, platform enhancements, and defect remediation, ensuring alignment with Product-Oriented Thinking and Delivery (POTD) principles and business outcomes.
• Partner with engineering and platform teams to identify, troubleshoot, and resolve data availability, data quality, and platform integration issues impacting data science and analytics use cases.
• Define and monitor adoption, performance, and value realization metrics associated with data science platform modernization and migration efforts.
• Advocate for data management best practices, governance requirements, and operational excellence to ensure trusted, scalable, and compliant use of enterprise data assets.
• Develop and maintain the data product roadmap; scopes and prioritizes activities based on the CDO, 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
• Define requirements for the Data Technology team on data processing and storage to facilitate a variety of 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
• Act as a product evangelist to build awareness, understanding, adoption, and buy-in
• Support the company’s commitment to risk management and protect the integrity and confidentiality of systems and data.
• Oversee the integration of strong data governance, risk and security controls.

Benefits

• Healthcare Coverage – Competitive medical (PPO/HDHP), dental, and vision plans as well as company contributions to your Health Savings Account (HSA) or pre-tax savings through flexible spending accounts (FSA) for commuting, health & dependent care expenses.
• 401(k) Retirement Plan – Featuring a 100% Company Safe Harbor Match on your first 6% deferral immediately upon eligibility.
• Paid Time Off – Flexible Time Off for Exempt (salaried) employees, as well as generous PTO for Non-Exempt (hourly) employees, plus 11 paid company holidays and a paid volunteer day.
• 12 weeks of Paid Parental Leave
• Maven Family Planning – provides support through your Parenting journey including egg freezing, fertility, adoption, surrogacy, pregnancy, postpartum, early pediatrics, and returning to work.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior