Why This Job is Featured on The SaaS Jobs
This AI Productivity Analyst role stands out in SaaS because it sits at the intersection of internal operations and product-adjacent enablement, where GenAI adoption is increasingly becoming a competitive lever. Rather than building models from scratch, the remit centers on evaluating third-party AI and ML tools and translating them into measurable workflow improvements across core SaaS functions like Engineering, Customer Success, and FP&A.
For a SaaS career path, the work offers repeated exposure to the full lifecycle of practical AI deployment: identifying bottlenecks, running structured pilots, quantifying ROI, and tracking adoption against KPIs and OKRs. That blend of experimentation and business measurement maps closely to how modern SaaS organizations scale efficiency, making the experience portable across companies that are formalizing AI transformation programs.
The role is best suited to early-career operators with a technical foundation who prefer cross-functional problem solving over a single-discipline track. It rewards comfort with ambiguity, an evidence-led approach to testing, and the ability to communicate findings to senior stakeholders. Candidates interested in how SaaS teams actually change day-to-day work through tooling, not just strategy, should find the scope aligned.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Your Role
As an AI Productivity Analyst, you’ll own a critical role in scouting, evaluating, testing, and piloting third-party AI tools to unlock significant productivity gains across Dialpad. You’ll work closely with the Head of AI Transformation and functional leads from Engineering, Design, Marketing, Customer Success, and FP&A to map high-value process bottlenecks and identify AI solutions. You’ll also help create structured experiments and pilot programs that demonstrate measurable business impact. In addition, you’ll help bring cutting-edge AI technology into practical application, supporting implementation and tracking success to drive our internal AI transformation.
This position reports to our Head of AI Transformation.
What You’ll Do
- Partner with functional leads in Engineering, Design, Marketing, Customer Success, and FP&A to map high-value process bottlenecks.
- Research, shortlist, and demo external GenAI & ML products that can automate or accelerate those workflows.
- Design and run structured experiments (PoCs, A/B tests, pilot roll-outs) to quantify productivity impact and user adoption.
- Develop and present ROI models, providing actionable recommendations to senior leadership.
- Support implementation (including light configuration, prompt engineering, and user training) of selected solutions.
- Track business unit KPIs and OKRs post-deployment; iterate with partners and vendors to hit or exceed the 20% productivity target.
Skills You’ll Bring
- Bachelor’s degree in Computer Science or comparable technical degree, with a minor or demonstrated interest in Business Analytics, Data Science, (applied) AI, or related fields.
- 1-2 years of relevant experience.
- Demonstrated hands-on fluency with GenAI tools (e.g., Gemini, ChatGPT, Claude, Grok, etc.) in personal or academic projects.
- Solid understanding of AI technologies, machine learning concepts, and their applications in business settings.
- Analytical mindset: able to design experiments, interpret metrics, and separate signals from noise.
- Clear, concise communicator comfortable distilling technical findings for non-technical stakeholders.
- Curiosity, bias for action, and ownership mentality in a fast-moving, ambiguous environment.
- Nice-to-have: experience with SaaS integrations (Zapier, APIs) or low-code automation platforms.
- Solid foundation in Python or SQL; familiarity with data-viz dashboards (Tableau, etc.).
