Are you ready to revolutionize the advertising industry?

At Cognitiv, we are not just another AdTech company—we are industry trailblazers redefining media buying with our Deep Learning Advertising Platform. Since 2015, we have harnessed the power of cutting-edge deep learning technology and data science to transform how brands connect with their customers. Our mission? To bring intelligence to advertising and deliver unparalleled precision, relevance, and impact at scale.

With our innovative platform, advertisers enjoy unprecedented flexibility—whether it is activating Dynamic Deals through their preferred DSP, leveraging our managed service DSP, or utilizing our industry-first ContextGPT product. As a part of Cognitiv, you will be at the forefront of AI-driven advertising solutions, driving change and achieving remarkable growth in a rapidly evolving industry.

Now, we’re growing!

The Role

At Cognitiv, we're building the next generation of finance. As our first Finance & AI Analyst, you'll combine financial expertise with hands-on technical skills to transform how Finance accesses data, builds reporting, and makes business decisions.

With a next gen ERP platform, a new order management system, and an evolving data stack, you'll build the automation, reporting, and analytical capabilities that enable Finance to move faster and make smarter decisions. You'll use SQL and Python to pull, transform, and structure data, work directly with APIs and technical documentation to connect platforms, and leverage AI to accelerate development and scale what you build.

Alongside building these capabilities, you'll own core financial planning and analysis responsibilities, including budgeting, forecasting, cash flow management, and executive reporting. You'll have the opportunity to shape how Finance operates at a growing technology company, with significant ownership over both the financial analysis and the systems that support it.

This is an ideal opportunity for someone who enjoys building systems from the ground up, is excited by automation workflows, and wants to redefine how Finance operates and strategizes inside a fast-growing technology company.

This position will be located in New York City with a hybrid work schedule of 3 days in office (Monday–Wednesday) and 2 optional remote days (Thursday–Friday).

What You'll Do

Build and Automate Finance Data Workflows: Use SQL and Python to query, transform, and validate data across our data warehouse, ERP, order management system, and advertising platforms. Work directly with API documentation to understand how systems expose data and build workflows that connect platforms, automate recurring processes, and make reporting reliable, repeatable, and scalable. Leverage AI to accelerate development and reduce manual work across the Finance function.

Decision Support & Reporting: Develop on-demand reporting and analytical tools that provide real-time visibility into company performance. Produce board and executive reporting packages and forward-looking analyses that support strategic decision-making, including product mix and profitability.

Planning & Forecasting: Lead the annual budgeting process and maintain the company's three-year financial model. Partner closely with HR on headcount planning, compensation forecasting, and workforce modeling, while conducting scenario analyses to support strategic business decisions.
Cash Flow & Corporate Finance: Own weekly cash positioning, liquidity planning, and cash flow forecasting to support corporate finance activities and ensure proactive cash management.

Who You Are

The Foundation: Bachelor's degree in Finance, Accounting, Economics, or a related field.
Finance First: 3 to 5 years of experience in FP&A, corporate finance, strategic finance, or another highly analytical finance function.
Strong SQL Skills: Comfortable independently querying a data warehouse and working with complex datasets. You can join data across multiple tables, transform and aggregate data, investigate discrepancies, and build the queries needed to answer business questions without relying on a data team for every request.