Available Locations: Austin, TX - Hybrid
About the team The Data Intelligence & Analytics organization builds the core data platform and internal products that power decision-making across the company. We design and operate large-scale data systems, own the company's data lake, ingestion infrastructure, and platform tooling, and develop end-to-end applications that transform complex datasets into fast, reliable, business-critical products used daily by go-to-market, product, and engineering teams. Our work sits at the intersection of data platforms, distributed systems, and product development, giving engineers the opportunity to own meaningful problems across the stack and build systems that truly run the business.
About the role You will focus on building scalable, reliable AI/ML models, services and GenAI powered application backends, partnering closely with data and full-stack engineers to deliver new features and operate the pipelines and platforms behind our products. Our stack spans multiple languages and technologies, including Python, React, and TypeScript, and continues to evolve. Many of our applications also incorporate strong AI components, giving you opportunities to work with modern AI infrastructure and tools such as vector databases, MCP-based services, and Workers AI.
You will focus on building scalable, reliable services and application backends, partnering closely with data and full-stack engineers to deliver new features and operate the pipelines and platforms behind our products. Our stack spans multiple languages and technologies, including Python, React, and TypeScript, and continues to evolve. Many of our applications also incorporate strong AI components, giving you opportunities to work with modern AI infrastructure and tools such as vector databases, MCP-based services, and Workers AI.
What youll do Partner and align with business leaders, stakeholders, product managers and internal teams to understand the business and product challenges and goals and address them using predictive analytics in a globally distributed environment.
Understand data landscape i.e tooling, tech stack, source systems etc. and work closely with the data engineering team to improve the data collection and quality.
Understand business/product strategy and high-level roadmap and align analysis efforts to enable them with data insights and help achieve their strategic goals.
Strong audience focused presentation and storytelling skills focused on key takeaways in a crisp and concise manner.
Define, implement, and train statistical, machine learning, deep learning and generative AI models.
Use software engineering best practices to publish model scores/insights/learnings at scale within the company.
Ability to define and spot macro and micro levels trends with statistical significance on a regular basis and understand key drivers driving those trends.
Active role in hiring, growing, and mentoring the data scientist team in Austin.
Examples of desirable skills, knowledge and experience M.S or Ph.D in Computer Science, Statistics, Mathematics, or other quantitative fields.
5+ years of data scientist experience with proven industry experience in a large scale environment (PBs scale & globally distributed teams).
Strong experience working with business functions such as Finance, Sales, and Marketing to build models and drive impactful business outcomes (eg: customer and revenue growth).
2+ years experience with a fast-growing SaaS business based company is preferred.
Strong experience in scientific computing using Python.
Experience with Spark, SQL, Tableau, Google Analytics, BigQuery (or any other Big data/Cloud equivalent) etc.
Experience working with and processing structured, unstructured, and semi-structured data.
Strong cross-functional collaboration experience with data engineering and data analysts teams within the function.
Proven track record of applying data insights and machine learning in order to address business needs and drive revenue.
Proficiency in large language models and the frameworks (Langchain, Langgraph, etc.) necessary for implementing GenAI applications, such as AI Agents, chatbots and related use cases.
Strong communication and presentation skills catered to different audiences within the company.
Capable of working closely with business, engineering, and product teams to ensure data initiatives are aligned with business needs.
Experience in hiring data scientists and establishing team best practices is preferred.