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.
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.
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.)
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 learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
Experience deploying machine learning models to production environments
Experience working with production relational databases as well as data warehouses on platforms such as Redshift - bonus for experience with NoSQL databases like Mongo
Comprehensive knowledge of advanced SQL techniques
Experience with data modeling including dimensional modeling for data warehouses
Working knowledge of latest AI models and their applicability to solve business problems
Proven track record of leading successful data projects that have made a positive business impact
Ability to explain complex data scientist concepts to engineers, product managers and other non-data scientist team members
Competitive compensation including an organization-wide goal-based bonus
Paid Time Off: 5 Weeks PTO upon joining + Winter Holiday Break. Each year with the company, you’ll receive 2 additional PTO days
80% Work Option: Work with your manager to choose between working 5 day weeks (standard full-time) or 4 day weeks @ 80% pay
Paid Parental Leave for primary and secondary caregivers
Sabbatical: After 5 years with the team, you’re eligible for a 1 month paid sabbatical
Healthcare (US residents): Medical, Dental, Vision with HSA option (US residents), Dependent care FSA (US residents)
401k (US residents): We match 6% contributions with immediate vesting
Build a house you want to live in - Examine long-term thinking and action
No BS - Practice transparency and honesty, especially when it’s hard
Invest in each other - Build successful relationships with your coworkers and customers
Discipline equals freedom - Keep your word to yourself and others
Strive for greatness - Constantly challenge yourself and others
Listen to our CEO and Founder, Steli Efti, tell the story of Close’s journey in the $0-30m Blueprint.
Watch our culture video from our 2023 team retreat in Milan. Every year our entire team gathers in person to build connection, foster cross-functional collaboration, and have fun. In 2025, we’re headed to Paris, France.
Explore our product. Check out a video demo or try an interactive demo!
We ask a few role-specific questions as part of our application process. These questions are designed to help us learn more about you from the start so please answer each question thoughtfully. We see this as an opportunity to get to know you beyond your resume.
While we are excited by all the opportunities that generative AI has unlocked, we request that you refrain from relying exclusively on AI tools when completing an application, unless explicitly stated. Every application is read closely by humans and any obviously AI generated applications will be disregarded.
Regardless of fit, you can expect to hear back from our team with an update on the status of your candidacy.
If you progress to the interview process, you’ll receive a full outline of the role-specific interview process in your first touchpoint with us. We do our best to make the hiring process clear and human.
Originally posted on Himalayas
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