Senior Algorithms Engineer

About Keen

Keen Decision Systems is an AI-native MarketingOS that helps marketing and finance leaders connect marketing investment directly to P&L outcomes. Built on proprietary Bayesian regression and probabilistic modeling, Keen’s platform spans marketing mix modeling, media planning, and scenario optimization, and is moving toward a fully closed-loop agentic system that carries a decision from data to measurement to planning to execution. The methodology is grounded in a dataset covering 400+ brands and more than $42B in tracked media spend, giving Keen a view of marketing performance no single client or agency can see on its own.

Keen is different. As a Inc. 5000 Fastest-Growing Private Company and a Triangle Business Journal Top 10 Best Place to Work, we’re growing quickly. But our growth isn’t the only thing that differentiates us.

At Keen, we are proponents of a Conscious Culture. Conscious Culture is an environment built on purpose. A Conscious Culture means that time and effort have been invested into making sure that how our company operates is as important as our business outcomes. Because we work smarter Monday-Thursday, we’re able to offer all employees a three-day weekend.

 

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About the role

At Keen, the Senior Algorithms Engineer develops, deploys and improves the algorithms that run in Keen AI Cortex. You’re a software engineer first, with the understanding of mathematics, data, and inference to read a model spec, question it, and suggest changes the Principal Algorithms Architect hadn’t considered. You’ll work directly with the Lead Engineer, and Principal Algorithms Architect, taking modeling ideas from prototype to production code and contributing to the algorithms when you see a better path.

What you’ll do as the Senior Algorithms Engineer

• Own algorithmic features end-to-end across the next generation of Keen’s AI Cortex. Design, implement, test, ship, and watch them run in production.
• Pitch in on adjacent Python backend projects (Django and FastAPI APIs, AWS infrastructure) when a piece of work spans more than one service.
• Keep the engineering practices tight: code review, tests, CI gates, documentation, and a clean ticketed workflow.
• Use AI coding tools with judgment. Fast iteration is the point. So is catching the moments when the model is confidently wrong.
• Develop algorithms from business ideas and turn them into production code.
• Collaborate with others in the development of the solutions, including the ability to effectively push back when the implementation can be improved.
• Communicate clearly across Product, Research, and Engineering. Write the design doc, name the tradeoff, get the decision made.

What Tech Stack do we choose?

• Google Suite for mail / calendar
• Jira for project management
• PostgreSQL, SQLite, pandas, NumPy
• AWS, Docker, GitHub Actions, pytest
• Solvers such as Ipopt, GAMS
• Python 3+ Django, FastAPI, REST APIs
• Slack for internal communications

What expertise do the best Senior Algorithms Engineers for Keen have?

• 7+ years shipping production Python on a team
• Knowledge of inference methods, particularly in economics and business domains including time-series models (or more generally state-space modeling), probability modeling, and multivariate systems.
• Comfortable with the engineering basics: tests, CI, code review, documentation, and working out of tickets.
• Hands-on experience with AWS, Docker.
• Operates independently. Scopes own work, talks to stakeholders, makes judgment calls when no one else is available to make them.
• Writes and speaks clearly.
• Math foundation in linear algebra, probability, and statistics. Demonstrated ability to read and write mathematical specifications, interpret and improve documented solutions.
• Working knowledge of pandas and NumPy, with understanding of the use of these packages in implementing algorithms.

Nice-to-have:

• Marketing Mix Modeling (MMM) or another econometric background
• Bayesian inference experience
• Optimization exposure
• A track record of developing mathematical algorithms into shipped production systems.

Benefits of Working with Keen:

• Mentoring and training from people who’ve been doing this for years
• Hands-on work on Bayesian models, optimization, and the data engineering behind them, applied to a product real customers use
• A seat in conversations across departments and at company-wide meetings
• 4-day work week with 3-day weekends
• Fully remote within the United States