Data Analyst II
Acorns
| Company | Acorns |
| Category | Data & Analytics |
| Location | Remote |
| Remote | Remote |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 10 Jul 2026 |
| Last verified | 31 Jul 2026 |
| Source | Employer career page (ashby) |
Description
AT ACORNS, OUR MISSION IS TO LOOK AFTER THE FINANCIAL BEST INTERESTS OF THE UP-AND-COMING, BEGINNING WITH THE EMPOWERING, PROUD STEP OF MICRO-INVESTING. HOW DO WE ACCOMPLISH OUR MISSION? OUR VALUES.
Lead With Heart - With compassion, integrity, and tenacity, inspire yourself and others to move past all previous thresholds of possibility
Make Bold Decisions - We are creating a new world. Be optimistic, adventurous, and courageous. Leap fearlessly into the future
Always Build Trust - Say what you mean, mean what you say, and do what you say you’re going to do. We are all owners. We are one team
Never Stop Growing - Change IS the constant. Stay hungry and curious. Be relentless in the pursuit of progress
Find a way - Never settle, no excuses, nothing is impossible. Just make it happen
Our values guide us, and our mission drives us. Come join us and help deliver financial wellness for the whole family, putting the tools of wealth-making into everyone’s hands.
Data Analyst II | Acorns
Acorns is seeking a Data Analyst II to own measurement, analyses, and experimentation across the customer journey, measuring campaign and experiment effectiveness, identifying new customer segments, uncovering opportunities for communication touchpoints that drive engagement, and evaluating what's working across product and lifecycle marketing. Every experiment you design, every audience you segment, every campaign you measure, and every insight you surface directly influences how customers start and engage with Acorns.
This is a strategic partner role, not a ticket-taker. You'll sit at the table with product managers, marketers, and engineers, advocating for measurement rigor, pushing back when experiment designs or attribution claims are flawed, and surfacing insights that change roadmaps and campaign strategies. We're looking for someone who has a point of view and isn't afraid to use it.
Acorns is a remote-first organization, offering the flexibility to work remotely while providing optional access to office space in Irvine, CA.
WHAT YOU WILL DO AT ACORNS:
- Own experimentation and analyses end-to-end: Partner with product and marketing teams to design A/B tests, measure campaign incrementality, determine sample sizes and duration, analyze results with statistical rigor, and translate findings into decisions. You ensure we're actually learning, not just reporting.
- Investigate when results don't add up: Dig into anomalies, validate tracking, segment results, and determine whether unexpected outcomes are signal or noise
- Surface insights proactively: Monitor performance, campaign results, and engagement patterns to identify opportunities and flag issues before they escalate.
- Connect metrics to customer outcomes: A statistically significant lift in click-through rate doesn't matter if it doesn't improve the customer experience or drive business value. You think about leading indicators, lagging indicators, and how to measure what actually matters.
- Shape Priorities and Infrastructure: Work with cross-functional teams to establish priorities, including new infrastructure and tool building that improves the team's analytical capabilities and scales measurement across the organization.
- Scale your impact with AI and automation: Use AI tools to accelerate analysis, generate code, and automate repetitive work. Contribute to the team's investment in agent-based workflows and AI-driven automation.
WHAT YOU WILL BRING TO ACORNS:
- 5+ years of Analytics experience preferably supporting product or marketing.
- Measurement and experimentation experience: You've designed experiments or measurement frameworks, calculated sample sizes, analyzed results with proper statistical methods, and communicated findings to non-technical stakeholders.
- Strong statistics foundation: Hypothesis testing, p-values, confidence intervals, Type I and Type II errors, and statistical power.
- Familiarity
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