60 applicants

Company

Vibrant Emotional Health · 1 day ago

Lead Product Manager, Data and Analytics

United States

Full-time

Remote

Senior Level

$124K/yr - $145K/yr

6+ years exp

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Responsibilities

Develop and communicate the product vision and roadmap for data and analytics tools, aligned with customer needs and organizational goals.

Build and scale capabilities in both product analytics and data-driven features, ensuring the organization has robust tools for decision-making and insight generation.

Identify and drive opportunities for new data products, including dashboards, datasets, and predictive analytics solutions.

Establish and lead a product analytics function, including managing a data analyst / PM and working closely with the Data team for engineering and reporting needs.

Develop frameworks for tracking, analyzing, and reporting on product performance, user behavior, and KPIs.

Design data sets, dashboards, reports, and experimentation tools to empower data-driven decision-making across internal teams and external stakeholders / users.

Act as a hands-on contributor during the team-building phase, balancing leadership with direct contributions to analytics and data visualization.

Build, lead, and mentor a small team, including a data analyst and external contributors, fostering a collaborative and high-performing culture.

Establish best practices for analytics and data product management, ensuring processes are scalable and customer-focused.

Provide regular feedback and professional development opportunities for team members.

Champion a customer-centric approach, ensuring that all data products and analytics solutions address real user needs.

Leverage data to inform product development, identify opportunities, and measure success through key metrics.

Lead A/B testing, experimentation, and segmentation to optimize product features and user experiences where relevant.

Partner closely with engineering, data, design and business teams to deliver valuable, high-quality, data-powered products.

Work with the Data team to align on data engineering, ETL processes, reporting infrastructure, and data governance requirements.

Collaborate with senior leadership to present findings, insights, and recommendations for improving product performance.

Oversee the end-to-end lifecycle of analytics and data products, from ideation to launch and continuous improvement.

Identify and address data gaps by working with the Data team to ensure data quality, availability, and accessibility.

Translate customer and business requirements into scalable data solutions that align with organizational goals.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data analyticsA/B testingData visualization toolsProduct managementETL processesData governanceProject managementStrategic thinking

Required

6-8+ years of experience in product management and/or product analytics with at least 2 years managing product managers or analysts.

Demonstrated experience delivering successful analytics products, including dashboards, visualizations, and workflows.

At least five years of experience managing product analytics functions, including developing dashboards, conducting analyses, and leading A/B testing.

Hands-on expertise with data visualization tools (e.g., Tableau, Looker) and familiarity with data platforms (e.g., Snowflake, Databricks).

Experience collaborating with data / data engineering teams to build and maintain reporting and analytics infrastructure.

Excellent leadership and team management skills, with experience mentoring product managers or data analysts.

Strong understanding of data analytics, A/B testing, experimentation methodologies, and user experience research.

Exceptional communication skills, with the ability to present complex ideas clearly and persuasively to technical and non-technical stakeholders.

Strategic thinker with a customer-first mindset, capable of balancing immediate needs with long-term vision.

Strong organizational and project management skills, with the ability to manage multiple priorities and stakeholders.

Familiarity with data engineering concepts, including ETL processes and data governance best practices.