About Us

Close is a bootstrapped, profitable, 100% remote, ~100 person team of thoughtful individuals who prioritize taking ownership and making a meaningful impact. We’re eager to make a product our customers fall in love with over and over again.

We 💛 small scaling businesses. Since 2013, we’ve been building a CRM that focuses on better communication, without the hassle of manual data entry or a complex UI. We are out to supercharge sales productivity with the most modern, thoughtfully designed all-in-one, communication-focused CRM.

We have minimal ML tech currently deployed, so a primary goal for this new role is to help design and implement our ML architecture for the future. That will require pulling data from our existing backend tech stack. This consists primarily of Python Flask web apps with our TaskTiger scheduler handling many of the backend asynchronous task processing chores. Our data stores include MongoDB, PostgreSQL, Redshift and Elasticsearch. The underlying infrastructure runs on AWS using a combination of managed and unmanaged services. We have a data warehouse that we use internally to evaluate app usage patterns, perform cost/pricing analysis and other business intelligence efforts.

Our product development process is inspired by Shape Up. We love open sourcing our code and ideas on GitHub and on The Making of Close, our behind-the-scenes Product & Engineering blog. Check out our open source projects like TaskTiger, LimitLion, SocketShark and ciso8601.

About the Role

We’re seeking a self-driven individual eager to take on this new role and make an impact by helping us harness our data to build better product features. We’re excited to apply statistical analysis, machine learning and a healthy dose of LLMs to create data-driven features that further boost our customers’ productivity. This is a new role at Close, so you’ll need to leverage your skill set and experience to drive these initiatives forward.

You will be joining our Data Insights team, one of our six cross-functional product teams. You will be regularly collaborating with backend & frontend engineers, product managers, designers and other teams as we turn new ideas into product features. The primary focus of this role is to help build better data enabled features but we do expect there to be a few internal projects that could leverage data science techniques for our own BI purposes.

You will

• Collaborate closely with product, engineering and other teams to uncover new data-driven product capabilities

• Develop statistical and machine learning models to solve business problems

• Design and implement end-to-end data pipelines that normalize, manage quality issues and transform raw data into useful data sets for analysis, training and validation

• Work closely with our Backend and Infrastructure engineers to productionize ML models and pipelines

• Perform feature engineering with existing and external data sources to develop optimal features for training our models

• Instrument our data processing infrastructure to ensure its health by monitoring its performance, availability and other operational parameters.

• Define and advance data science best practices within our engineering and product teams

• Ensure data integrity, quality, and security

• Add your data expertise to help improve our AI efforts (e.g. fine tuning, improved RAG data sources, etc.)

You have

• 5+ years of experience as a ML Engineer or Data Scientist solving meaningful business problems - Ideally some/all of this experience is at a Senior or Staff level

• Extensive experience with Python and working knowledge of software development methodologies

• Extensive experience with machine l