How to apply for Senior Product Manager-CX

About Bidgely

Bidgely uses appliance-specific analytics to help households cut energy use. The company operates at the intersection of climate impact, utility clients, and data science. This is a fit for someone who wants to build data products that reduce energy consumption at scale.

About the role

You will own a customer problem area end-to-end, from vision and strategy through PRDs, delivery, and measurable outcomes. The work spans data integrations, data engines, and multi-channel UX, with direct exposure to utility clients and regulators. Success is measured by adoption, CSAT/NPS, call deflection, savings, and reliability SLOs.

A typical day

A typical day may include reviewing data and experiment results, writing or refining a PRD, and working with design and engineering on incremental delivery. You may also meet with utility clients or internal execs to communicate trade-offs and decisions in writing. Ask the hiring team how they split time between discovery, delivery, and client-facing work.

Who Bidgely is looking for

• 4–7+ years in product management with SaaS and data/analytics products, including 2+ years owning a CX or engagement or data-driven product.
• Technically fluent enough to read APIs, reason about data models, eventing, and privacy/consent implications, and work closely with data scientists and engineers.
• Has shipped multi-quarter roadmaps with measurable outcomes and built scalable processes, not just one-off features.
• Comfortable running experiments, A/B tests, and iterating based on adoption, CSAT/NPS, call deflection, savings, and reliability SLOs.

Tips for this application

• Use your resume to show at least one product you owned end-to-end for 2+ years in a CX, engagement, or data-driven area.
• Name specific metrics you moved in past roles, such as adoption, CSAT/NPS, call deflection, savings, or reliability SLOs, since these are the outcomes Bidgely tracks.
• Describe how you worked with data scientists and engineers on data integrations, data models, eventing, or multi-application channel UX.
• Include one example of writing PRDs or specs and partnering with design on accessible, intuitive UX across channels.
• Mention any experience with utility clients, regulators, or pre-sales narratives, since the role includes representing the product externally.

What to cover in your cover letter

['A specific product you owned end-to-end, including the vision, strategy, metrics, and 6–12-month roadmap.', 'How you used market analysis, customer interviews, data mining, or experiments to prioritize what to build.', 'A concrete example of shipping incrementally with engineering and data science, including data integrations or data engines.', 'How you measured outcomes like adoption, CSAT/NPS, call deflection, savings, or reliability SLOs and iterated.']

Research before applying

• Read Bidgely's product pages on appliance-specific analytics and home energy savings to understand what the product does.
• Look for Bidgely case studies or public materials with utility clients to see how the company positions itself to utilities.
• Check how Bidgely describes data privacy and consent, since the role requires reasoning about privacy and consent implications.
• Find any public talks, blog posts, or interviews from Bidgely's product or data science team to understand their approach to data engines and multi-channel UX.

Likely interview topics

Based on the job description, expect questions about:

• How you would define the vision, strategy, and metrics for a customer problem area in home energy analytics.
• A time you used customer interviews, data mining, or experiment results to prioritize a roadmap.
• How you have partnered with data scientists and engineers on data integrations, eventing, or privacy and consent implications.
• How you design and run A/B tests, and which metrics you use to decide whether to iterate or stop.
• How you would enable GTM with positioning, packaging, and launch plans, and support pre-sales narratives with utility clients.

Common mistakes to avoid

• Applying without a clear example of owning a product end-to-end, since this role requires defining vision, strategy, metrics, and delivery.
• Focusing only on feature delivery and not on measurable outcomes like adoption, CSAT/NPS, call deflection, savings, or reliability SLOs.
• Claiming technical fluency without evidence of working with APIs, data models, eventing, or privacy and consent implications.