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Sales & Customer Success Analyst at Bottomline, Portsmouth, NH

Sales & Customer Success Analyst at Bottomline in Portsmouth, NH. Full-time. Est. up to $130k. Apply with swipeandhired.

Why Choose Bottomline?

Are you ready to transform the way businesses pay and get paid? Bottomline is a global leader in business payments and cash management, with over 35 years of experience and moving more than $16 trillion in payments annually. We're looking for passionate individuals to join our team and help drive impactful results for our customers. If you're dedicated to delighting customers and promoting growth and innovation - we want you on our team!

Work Authorization

Candidates must be authorized to work in the United States on a full-time basis without restriction. Visa sponsorship or transfers are not available for this position.

Role Summary

The AI Enablement Analyst will support Revenue Operations by helping bring AI-powered tools, agents, analytics, and automation into the day-to-day workflows of Paymode's Sales organization.

This is a hands-on role at the intersection of Sales, Revenue Operations, data, and AI. You will help identify high-impact AI use cases, prepare and structure trusted data, deploy and test AI-enabled solutions, and drive adoption across revenue-generating teams.

You will serve as a bridge between Sales stakeholders, Revenue Operations, data teams, and AI technologies, translating business needs into practical, scalable solutions. Your work will help ensure the data powering AI models and automations is accurate, governed, and reliable while enabling faster insights, reducing manual work, and improving how our teams operate.

This is an opportunity to directly influence how people, data, AI, and technology come together to support revenue growth.

How you'll make an impact:

Identify and implement AI and automation use cases that improve Sales and Revenue Operations workflows, reporting, and efficiency.

Support the end-to-end deployment of AI agents for Sales teams, including use-case definition, requirements gathering, testing, deployment, and adoption.

Prepare, structure, and maintain data used by AI applications, including reusable datasets and semantic models.

Monitor and improve data quality, consistency, and governance to support trusted AI-driven insights.

Enable AI-powered and self-service analytics that help business users access insights and make decisions more quickly.

Partner with Sales, Revenue Operations, and technical teams to translate business challenges into scalable data and AI solutions.

Evaluate and prioritize AI and automation opportunities based on business need, feasibility, and potential impact, with a focus on reducing manual processes and scaling Revenue Operations capabilities.

Ensure AI initiatives align with enterprise governance, risk, security, and compliance standards.

Validate AI-generated outputs and help establish processes for monitoring accuracy, reliability, and business value.

What will make you successful:

0–3 years of experience in data analytics, business intelligence, Revenue Operations, business analysis, or a related field. Relevant internships, co-ops, academic projects, and hands-on AI/data projects may also be considered.

Working knowledge of SQL and foundational understanding of data modeling, with the ability to work effectively with structured datasets.

Experience or hands-on exposure to structured datasets and data-driven solutions through professional, academic, internship, co-op, or project-based work.

Experience or exposure to business intelligence and data platforms such as Power BI, Snowflake, or similar technologies.

Exposure to AI tools and technologies, including Microsoft Copilot or similar generative AI tools, AI agents, natural-language querying, AI-assisted analytics, or AI-powered workflow automation.

Ability to evaluate an AI use case from initial business need and experimentation through testing, deployment, and adoption.

Awareness of data quality and responsible AI considerations, including governance, risk, security, and compliance.

Strong analytical and problem-solving skills, with the ability to translate business requirements into practical technical solutions.

Strong communication skills and the ability to collaborate effectively with both business and technical stakeholders.

Preferred Qualifications:

Experience supporting Sales, Revenue Operations, or other revenue-generating teams.

Experience enabling self-service analytics or working with semantic models.

Familiarity with enterprise data architecture and data governance frameworks.

Experience piloting, testing, or scaling AI and automation use cases within business operations.

Experience working in a business analyst or data analyst capacity within SaaS, FinTech, or Payments.

Exposure to sales technology, CRM, or Revenue Operations platforms.

Core Competencies:

Intellectually curious: Eager to explore emerging AI capabilities and continuously learn how they can improve Sales workflows.

Critical thinker: Validates AI-generated outputs, questions assumptions, and understands that AI is a tool rather than the answer to every business problem.

Business-minded: Connects AI and data capabilities to meaningful business outcomes.

Collaborative: Comfortable partnering across Sales, Revenue Operations, data, and technology teams.

Self-starter: Comfortable operating in ambiguity and helping define solutions where an established playbook may not yet exist.

Execution-oriented: Able to move from ideas and experimentation into practical, usable solutions.

Adaptable: Comfortable working in a quickly evolving AI and technology landscape.

We welcome talent at all career stages and are dedicated to understanding and supporting additional needs. We're proud to be an equal opportunity employer, committed to creating an inclusive and open environment for everyone.