Product Manager

Credibly is building improvements across its lending platform, and this Product Manager role helps drive product planning and execution from discovery through launch. Based out of our Southfield, MI headquarters with a hybrid schedule, you will report to the VP of Product and own outcomes, KPIs, and cross-functional delivery for merchant, broker, and internal experiences.

What you’ll get

• Hybrid work schedule based out of Southfield, MI
• 4 weeks of PTO on day one
• 8 paid company holidays
• Paid parental leave, bereavement, and jury duty
• 401(k) with company match (100% vested after 2 years)
• Medical insurance through BCBSM or BCN
• Dental and vision through BCBS
• HSA and FSA available, including LPFSA and Dependent Care
• Company-paid life insurance and short-term disability
• Additional optional insurance coverage

Compensation

The expected base salary range for this role is $110,000–$140,000, depending on experience and skills. [Confirm with HR and add bonus/equity details if applicable.]

How you’ll drive impact

• Define goals and KPIs for product areas, including conversion, time-to-fund, operational efficiency, and partner and merchant satisfaction.
• Lead product initiatives from ideation and discovery through requirements, design, testing, launch, and iteration.
• Spend time with merchants, ISO and broker partners, and internal teams to understand workflows and pain points, then turn learnings into clear problem statements.
• Evaluate third-party data, verification, and banking-data providers using hit rate, lift, latency, reliability, and cost; build the business case for adding or replacing providers; and manage integrations with funding and capital markets partners.
• Document vision and scope using use cases, PRDs, epics, and user stories so agile teams can build the right solution.
• Partner with engineering, design, and data to ensure solutions are usable, technically sound, and secure.
• Use SQL and BI tools to size opportunities, understand behavior, and measure the impact of what ships.
• Identify manual work and decision points where automation, integrations, or AI can add value, and coordinate delivery responsibly.
• Coordinate launch plans with sales, marketing, operations, and support, including training, FAQs, and documentation to drive adoption.
• Define acceptance criteria, support testing and UAT, and work with business and engineering teams to triage and resolve issues.
• Stay current on the alternative lending and fintech landscape, competitor offerings, and emerging technology.

What you bring

• 4+ years of product management experience delivering software products, ideally in B2B, fintech, or financial services.
• A track record of shipping products that produced measurable business results.
• Strong discovery and prioritization skills, with judgment to balance customer, business, and technical needs.
• Experience using AI tools day to day (for example, drafting user stories, summarizing feedback, or analyzing data) and the judgment to double-check outputs.
• Comfort with data; working knowledge of SQL and BI tools is strongly preferred.
• Technical fluency to collaborate with engineers, including understanding APIs, integrations, and system design at a high level.
• Practical familiarity with AI tools and how they are used in products and workflows.
• Experience working in agile teams with Jira/Confluence or similar tools.
• Excellent written and verbal communication and the ability to align stakeholders across functions and levels.
• Bachelor’s degree or equivalent practical experience.

Technologies you’ll use

SQL, BI tools, Jira, Confluence, Metabase, Plaid, PRDs, use cases, epics, user stories, UAT, Python

What makes you special (preferred)

• Experience in small business lending, MCA, credit underwriting, KYB/KYC, or fraud operations.
• Experience with third-party integrations common in lending, such as bank-data providers (including Plaid), credit reporting agencies, and KYC/KYB verification vendors.
• Experience with BI tools such as Metabase.
• Experience working with data science teams on products that use machine learning models, including writing requirements, testing model changes, and tracking model performance after release.
• Using genAI for basic Python or scripting ability for data checks and test automation.