About

Daylit is a leading AI agent platform for accounts receivable. Our platform automates the manual work of collecting and reconciling invoices so finance teams can scale credit and collections teams without adding headcount. Our customers trust Daylit to deliver a complete view of portfolio health — surfacing at-risk accounts, predicting payment timing, and powering accurate cash flow forecasts. Companies with high invoice volume use Daylit to reduce DSO, eliminate repetitive work, and know exactly when cash will hit the bank.

The Role

We are seeking an AI Deployment Co-op to join our Boston-based Operations and Client Success team. In this role, you will support the deployment, optimization, and evaluation of Daylit’s AI-powered products, working with customer data and AI outputs to improve performance and drive successful implementations. You’ll gain hands-on experience applying data science and AI in a real-world fintech environment while collaborating closely with Product, Engineering, and Client success teams.

What You’ll Do

AI Deployment & Operations:

• Support the deployment, configuration, and optimization of Daylit’s AI-powered products across customer environments.

• Analyze customer data and workflows to identify opportunities for automation and effective AI implementation.

• Test and evaluate AI outputs, identifying patterns, edge cases, and opportunities to improve performance.

• Collaborate with Product, Engineering, and customer-facing teams to troubleshoot issues and improve deployment processes.

• Assist day to day client enquiries and host client success office hours

Data Analysis:

• Use Python, SQL, Excel, and other analytical tools to analyze customer, product, marketing and AI performance data.

• Build datasets and analytical frameworks to evaluate AI outputs and deployment effectiveness.

• Translate data-driven findings into actionable recommendations for internal teams and external clients.

What We’re Looking For

• Strong interest in artificial intelligence, machine learning, and data science, with experience using Python, SQL, Excel, or similar analytical tools.

• Strong analytical, problem-solving, and communication skills with a high level of attention to detail.

• Ability to work independently, take ownership of projects, and thrive in a fast-paced startup environment.