Senior Analytics Engineer

The posting, as January wrote it

Collections today works like an emergency room. The doctors carry too many patients, everyone arrives at their worst moment, and nobody has their chart. We're making it primary care. January personalizes interactions and optimizes decisions across every stage of consumer credit. We started in the hardest, most broken stage, because if it works there it works anywhere.

Most consumers want to pay what they owe. They want a way out, not a break. We've serviced over $20 billion in debt across more than 20 million consumers. We see more people with charged-off loans each year than all but the top five US banks. Those consumers rate us about 50% higher than the banks that lent them the money. Creditors net over 30% more because we collect more and charge less.

Most AI strips the human out of the work. We use it to make someone's hardest financial moment more human. The more human we make it, the more people recover. Now we're moving upstream, catching people before they default and building across every stage of the consumer credit lifecycle. The consumer in collections today is the consumer who gets approved tomorrow.

ABOUT THE ROLE

As January's Senior Analytics Engineer, you'll own the layer that makes our data trustworthy — for the people who use it today, and for the AI agents that will increasingly use it tomorrow. Data Engineering gets raw data reliably into Snowflake; you take it from there. You'll build and govern our semantic layer, standardize how teams across January define and measure success, and make sure that a metric means the same thing whether it's surfaced on a dashboard, in a Slack chatbot, or by an LLM answering a question on someone's behalf. You'll partner with Data Engineering to deliver impactful client reports, and you'll advocate for the data January needs to capture, but doesn't yet. This is a foundational hire for a company betting that the future of analytics is fewer people writing one-off queries and more trust built into the data itself.

You will

• Own the gold layer and build January's semantic layer — designing the dbt-driven, Snowflake-native layer that becomes the single source of truth for every tool that answers a data question, from Sigma to a Slack chatbot to future LLM-based interfaces
• Define and enforce data contracts and standardized metrics — establishing clear ownership boundaries so gold-layer changes are intentional and communicated, and resolving cross-team disagreement about what a metric means
• Partner on our client reporting revamp — working alongside Data Engineering (who own the underlying pipeline architecture) to clarify metric definitions, define client success criteria, and build the gold-layer models the new reporting experience needs — including data products clients don't know to ask for yet
• Advocate to expand the data January captures — partnering with Analytics, Borrower Support, and Client Acquisition to close data-capture gaps (event granularity, structure

[…]
t calls get made by the people closest to them, not routed up a chain. You'll set the standards that let the team decide without you in the room.

• Speed beats perfection. You run tight loops, act at 70% on reversible calls and adjust as you learn. Fast loops beat slow ones.
• Candor beats comfort. You'd rather hear a hard truth early than a polite sidestep that wastes everyone's time.
• Writing beats the average meeting. Clarity scales.
• AI runs through everything here. 95% of our consumer interactions are AI-driven. Internally, we've built an LLM code reviewer and approver. We benchmark coding agents against real tickets so we can automate more of them. Over the last six months, Engineering has doubled how much we can ship. Non-technical teams are just as fluent in AI - anyone can spin up a custom LLM Slackbot, and everyone consistently builds AI tools and skills that are shipped org-wide.
• We operate at every altitude. No one here lives only on Mount Olympus, not even the leaders. We get into the trenches to learn the ground truth. We constantly refine our information flows so that our decisions are driven by the best, most up to date inputs.
• We build in person, at least three days a week in our office in Nolita, with a growing group coming in every day. Random run-ins cross-pollinate ideas. Face time builds trust no thread can. Building alongside people makes work far more fun.

As a New York City-based company, we are dedicated to transparent, fair, and equitable compensation practices that reflect our commitment to fostering an environment where all team members are valued and supported. We encourage individuals from all backgrounds to apply.

We are an equal opportunity employer committed to diversity and inclusion in the workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, age, veteran status, or any other legally protected characteristic.