Product Analyst

Overview

Join to apply for the Product Analyst role at Jot Psych
.

Click apply to see our full job listing.

Critical: if you don't apply via our Google Form, we won't look at your application. Read the "Application Process" steps in the full role description to learn more.

Behavioral health is in crisis. Demand is at an all-time high, and clinicians are drowning in admin work—often spending 3+ hours per day documenting sessions, chasing billing, and wrestling with their EHR.

Jot Psych
’s mission is to defeat admin work and let clinicians practice human-centered healthcare.

We already reduce note-taking time by ~90% for thousands of providers. Now we’re expanding into billing, scheduling, e-prescriptions and more.

We are looking for a Product Analyst to partner directly with our founders and product team in designing, running, and scaling Jot Psych’s analytics function. Your mission is simple: turn messy real world data into clear decisions by owning our metrics, experiments, and insight loops.

This is not a back office reporting role, and not a pure data engineering role. You will own the analytics process end to end: defining and instrumenting metrics, connecting data sources, designing and analyzing experiments, and turning what you learn into simple recommendations for product, growth, and customer teams.

You will thrive here if you:

• Are obsessed with experimentation, clear metrics, and iteration speed.
• Enjoy turning vague questions into concrete hypotheses, tests, and readouts.
• Can get into the weeds with SQL and Python while keeping the big picture in mind.
• Are as comfortable cleaning up an event schema as you are presenting insights in a roadmap meeting.

Data Foundations & Pipelines

• Consolidate and clean data across product events, Stripe, Hub Spot/Facebook, CRM, support tools, and other sources.
• Partner with engineering to tighten tracking and schemas so experiments, dashboards, and reports share a single source of truth.
• Connect data sources and set up simple, reliable data flows.
• Build and maintain dashboards for founders, product, Customer Success, and growth that show core metrics at a glance.
• Track key funnels and campaigns, including rewarming and customer success campaigns across channels like Facebook, Hub Spot, and email.
• Keep company-level reporting fresh so everyone can see how activation, conversion, retention, and revenue are moving over time.

Experiments & Product Analytics

• Design, run, and analyze experiments, including A/B tests on onboarding, features, pricing, and campaigns.
• Define and maintain core metrics (activation, trial → paid conversion, retention, churn, feature usage) and link behavior back to cohorts and segments.
• Surface clear narratives, predictors, and next steps from the data, including early signals of non-conversion or churn and what we should test next.

We are looking for a team member with strong analytical instincts, comfort with ambiguity, and a high bar for quality. This particular role requires rigor, curiosity, and the ability to move from raw data to clear decisions.

Here is more of what we are looking for:

• 3 to 6+ years of experience in a data or analytics role. Product analytics, growth analytics, or business intelligence in SaaS is ideal.
• Strong SQL skills and experience working with event level product data.
• Proficiency in Python for analysis, modeling, and working with APIs.
• Solid foundation in statistics, including experiment design, significance testing, confidence intervals, and basic regression.
• Hands on experience designing, running, and reporting on experiments, not just consuming someone else’s analysis.
• Experience building dashboards in a BI tool such as Metabase, Looker, Mode, or Tableau.
• Strong written and verbal communication skills, with comfort explaining complex analyses to non technical teammates.
• Highly organized with strong attention to detail, and able to move quickly without sacrificing quality.
• Experience with Statsig for experimentation and feature flagging.
• Experience with marketing or campaign measurement, for example Facebook, Hub Spot, or email re engagement campaigns.
• Some exposure to data engineering…