Senior 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. To learn more, please visit .About the Team Data is at the core of Outreach's strategy. It drives us and our customers to the highest levels of success. We use it for everything from customer health scores and revenue dashboards to operational metrics of our AWS infrastructure, to helping increase product engagement and user productivity through natural language understanding, to predictive analytics and causal inference via experimentation. As our customer base continues to grow, we are looking towards 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 success and efficiency of these workflows, and providing tools to support the optimization of these workflows. One example is predicting the likelihood of a deal to win so sales reps can shift their focus strategically toward deals that need attention. In addition to just producing a score as our prediction, we put emphasis on analyzing which factors during the sales process contributed more to the prediction. This allows us to give recommendations to the sales rep on what to do next.As a high-level contributor to the team, you will be part of a cross-functional team consisting of data scientists and machine learning engineers working on making our mission a reality.Your Daily Adventures Will Include: Design, implement, and improve machine learning Systems. Defining metrics to measure effectiveness of processes Contribute to machine learning applications end to end, from research to prototype to production. Work with product managers, designers, and customers to define vision and strategy for a given product. Our Vision of You: You have a degree in Computer Science, Data Science, or a related field with 8+ years of technical experience You have knowledge in statistics and machine learning and have practical experience applying it to solve real-world problems. You understand the typical lifecycle of machine learning product development, from inception to production. You have good experience in LLM based application development, LLM tuning and prompt engineering. You have worked with framework like Langchain, OpenAI Agent SDK. You have strong programming skills in at least one programming language (Python, Golang, etc.). Experience in GoLang is a plus. You have experience working with distributed data processing frameworks such as Spark. Experience with Spark's MLlib, Databricks, MLFlow are a plus You are hands-on, able to quickly pick up new tools and languages, and excited about building things and experimenting. You should be able to work alongside experienced engineers, designers, and product managers to help deliver new customer-facing features and products. We’re an equal opportunity employer. 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're dedicated to hiring the whole human, not just a resume. To that end, we look for a diverse pool of applicants-including those from historically marginalized groups. We would like to invite you to apply even if you don't think you meet all of the requirements listed below. We don't want a few lines in a job description to get between us and the opportunity to meet you.