Senior Data Scientist, Product Analytics

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 a Senior Data Scientist, Product Analytics, you'll play a significant role in shaping product direction through data analysis, visualization, modeling and experimentation. Working closely with product managers, your actionable insights will directly affect how our users get out of debt and back to financial stability.

You’ll act as a strategic partner to product managers at January, enabling them to continuously make data-driven decisions, run experiments, and evaluate how our most important success metrics are changing over time. You will become a subject matter expert in our data, making impactful recommendations to improve our product and processes.

You’ll also contribute to building January’s reputation as a data-focused collection agency that operates with sophistication and intentionality. You’ll work closely with the operations team, ensuring that our client success managers are informed and equipped to answer any question and handle any client conversation with ease.

What We Need

• At least 2 years of experience using SQL
• Experience using languages like Python or R to conduct statistical analysis
• Medium to advanced understanding of statistics as they relate to experimentation
• Able to present data in a compelling way to empower our product and engineering teams to make better decisions
• Able to think strategically and consider the impact of your work on January’s success as a whole
• Able to work independently: given context and some initial guidance, you’re able to do a deep dive and make insightful recommendations for the business

How We Work

• Decentralization beats control. The best 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.