Staff Data Scientist

About Outreach

Outreach, founded in 2014, is the only complete AI Revenue Workflow Platform that helps sales leaders benefit from connected account visibility, performance insights, and higher forecasting accuracy across every GTM team. Outreach infuses agentic AI to power 100s of use cases across sales motions. From new logo prospecting to renewal and expansion, Outreach AI automates workflows and frees sellers to focus on more strategic conversations and actions. Global organizations use Outreach to power their revenue teams, including SAP, Siemens, Snowflake, ZoomInfo, and Verizon to name a few. Data is at the core of Outreach's strategy. It drives us and our customers to the highest levels of

operational metrics of our infrastructure, to helping increase product engagement and user

productivity through natural language understanding, to predictive analytics and causal

new ways of leveraging our data to deeper understand our customers' needs and deliver new

products and features to help continuously improve their customer engagement workflows.

The mission of the Data Science team is to enable such continuous optimization by

reconstructing customer engagement workflows from data, developing metrics to measure the

As a member of the team, you will work closely with other data scientists, machine learning

Design, implement, and improve machine learning Systems.

Contribute to machine learning applications end to end, i.e. from research to prototype to production.

A hybrid AI engineer who can navigate both sides with little help from others

You understand the typical lifecycle of machine learning product development, from inception to production.

You have experience in developing and deploying GenAI based applications.

Experience with LangChain, LangGraph is a plus

You have experience building microservices. Experience with Golang is a plus

You have strong programming skills in at least one object-oriented programming language (Java, Scala, C++, Python, Golang, etc.)

You have substantial experience with building and managing infrastructure for deploying and running ML models in production.

You have experience working with distributed data processing frameworks such as Spark. Experience with Spark's MLlib, AWS, Databricks, MLFlow are a plus.

You have knowledge in statistics and machine learning and have practical experience applying it to solve real-world problems.

You are hands-on, able to quickly pick up new tools and languages, and excited about building things and experimenting.

You go above and beyond to help your team.

You should be able to work alongside experienced engineers, designers, and product managers to help deliver new customer-facing features and products.

You have degree in Computer Science, Data Science, or a related field, and 7-10 years of industry or equivalent experience.

All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

Our success is reliant on building teams that include people from different backgrounds and experiences who can elevate assumptions and ideas with fresh perspectives. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. If you would like more information about how your data is processed, please contact us.