Product Manager - Analytics

Product Manager – Analytics Department: Product Location: Hybrid – Remote + Office in Washington DC As a Product Manager at Ordway Labs, you will play a critical role in defining, developing, and managing all the analytics and reporting needs of Ordway billing and finance platform. You will collaborate with cross-functional teams to drive product innovation, ensure market fit, and deliver value to our customers. This role requires a strategic thinker with a strong understanding of product management principles and a passion for creating exceptional software solutions. Job Responsibilities Define and own the analytics product roadmap, aligning it with company data strategy and business priorities. Translate business intelligence needs into well-scoped, prioritized product requirements for dashboards, pipelines, and AI-powered analytics tools. Identify opportunities to leverage NLP, LLM-based agents, and intelligent automation to improve analytics workflows. Drive alignment across stakeholders — from data engineers and architects to executives and business unit leads. Cross-Functional Collaboration Serve as the bridge between technical data teams and non-technical business stakeholders. Partner with Data Governance teams to ensure compliance, security, and data quality standards are embedded in product decisions. Support go-to-market efforts for analytics tools, including training, enablement, and change management. Delivery & Execution Manage the analytics product backlog, running sprint planning, grooming, and retrospectives with data and engineering teams. Define KPIs and success metrics for all analytics features and track adoption, performance, and business impact post-launch. Oversee dashboard and visualization delivery, ensuring reports meet performance, usability, and governance standards. Champion documentation standards for data products, pipelines, and analytics architectures. AI & Intelligent Analytics Own the product vision for NLP-based analytics interfaces, conversational BI agents, and LLM-powered data tools. Define use cases for AI/ML integration — including document understanding, anomaly detection, and intelligent automation in analytics workflows. Collaborate with engineers to evaluate and integrate LLM-based features into existing analytics products (e.g., natural language querying, AI-generated summaries). Set guardrails for AI-generated insights — defining quality thresholds, evaluation metrics, and user-facing explainability requirements. Discovery & Requirements Conduct user research with business analysts, finance, operations, and leadership to surface unmet analytics needs. Author clear PRDs and user stories that data engineers, BI developers, and architects can act on immediately. Define acceptance criteria for SQL-driven reports, ETL pipeline outputs, and data warehouse deliverables. Partner with Analytics Architects to evaluate build-vs-buy decisions for data warehouse platforms (Snowflake, ClickHouse, Redshift) and visualization tools (Tableau, Power BI, Looker). Qualifications Preferred Python familiarity — able to read scripts and understand data transformation logic, even if not writing production code. Experience with real-time or streaming data products (Kafka, Spark) from a product ownership perspective. Familiarity with cloud data platforms (AWS, Azure, GCP) and associated managed analytics services. Experience with AI/ML-enabled product features — defining, launching, and evaluating models or LLM-based capabilities in production. Exposure to LLM applications (copilots, intelligent search, document understanding) particularly in finance or accounting contexts. Background in data governance, compliance, or data quality programs. Experience mentoring teams or running a center-of-excellence for analytics best practices. Required 5+ years of product management experience, with at least 2–3 years focused on data, analytics, or BI products. Strong SQL literacy — able to read, interpret, and review complex queries; comfortable discussing query optimization and data modeling trade-offs. Hands-on familiarity with data warehouse platforms such as Snowflake, Redshift, or ClickHouse. Experience managing BI/visualization products — Tableau, Power BI, Looker, or similar. Working knowledge of ETL/ELT concepts and data pipeline architectures. Demonstrated ability to write PRDs and user stories for data-intensive, technically complex products. Experience defining metrics and success criteria for analytics features and data products. Strong facilitation and communication skills — ability to run discovery workshops, present roadmaps, and manage stakeholder expectations at all levels. #J-18808-Ljbffr