Throughout our interview process, you’ll have the chance to demonstrate how you use AI to learn, iterate, and amplify your impact. If you’re excited to be part of a team that’s leading the way in AI-powered collaboration, we’d love to meet you.
We are looking for a Data Scientist who can help us move beyond using AI only as a coding assistant and toward using AI to design, build, evaluate, and improve AI systems. The company is moving toward Agentic AI, where LLMs, tools, workflows, and autonomous agents are combined to solve business problems, automate complex processes, and accelerate the creation of new AI capabilities. As a Data Scientist, you will work at the intersection of data science, machine learning, LLMs, agents, and automation. This role is ideal for someone who understands statistics and machine learning conceptually, can work hands-on with data and SQL, and is excited about building AI systems that help produce, test, and improve other AI systems. This is not only about using tools such as Claude Code, Codex, or similar systems to write code faster. It is about understanding how to use AI as part of the production process for AI itself.
In This Role, You Will
Use statistics and machine learning to analyze data, evaluate systems, and guide decision-making.
Build and evaluate LLM-powered workflows, agents, and AI automations.
Help design systems where AI can assist in generating prompts, tools, skills, workflows, tests, documentation, and model evaluations.
Develop evaluation frameworks for agentic workflows, including quality, reliability, accuracy, cost, latency, and failure modes.
Use SQL to extract, transform, and analyze data from business and product systems.
Work with Git-based workflows and collaborate with technical teams.
Contribute to AI workflows deployed or supported through GCP, such as BigQuery, Cloud Storage, Vertex AI, or related services.
Experiment with Claude Code, Codex, or similar AI development environments to accelerate AI system development.
Identify opportunities to automate repetitive analytical, operational, and software development tasks using agents.
Communicate technical findings clearly to business, product, and engineering stakeholders.
Here's What You Need
Bachelor’s degree in Data Science, Statistics, or a related quantitative field, or equivalent practical experience.
Master’s degree in Statistics, Data Science, Artificial Intelligence, Machine Learning, or a related field preferred.
5+ years of professional experience in data science, machine learning, or a closely related quantitative field.
Strong conceptual understanding of statistics, including distributions, uncertainty, hypothesis testing, regression, experimentation, and causal thinking.
Strong conceptual understanding of machine learning, including model evaluation, overfitting, feature engineering, supervised learning, unsupervised learning, and interpretability.
Proficiency with SQL.
Familiarity with Git and collaborative development workflows.
Some understanding of GCP or cloud-based data and AI infrastructure.
Experience working with LLMs, agents, or AI-assisted workflows. 1+ year of hands-on experience in a professional or research setting preferred.
Ability to think critically about AI outputs, limitations, hallucinations, evaluation, and reliability.
Interest in using AI not only as a productivity tool, but as a system-building capability.
This job posting is intended to comply with all applicable laws. If we learn during the course of our recruitment process that, due to an applicant’s location, further information about the position is required, including certain salary information, this information in this posting will be supplemented accordingly.
The estimated base salary range for new hires into this role is $120,000-150,000 annually + bonus depending on factors such as job-related knowledge, relevant experience, and location. We also offer a competitive benefits package, details of which can be found here.
Hybrid: 2 days in office
We are not able to offer sponsorship for this position
Physical Demands
Use statistics and machine learning to analyze data, evaluate systems, and guide decision-making.
Build and evaluate LLM-powered workflows, agents, and AI automations.
Help design systems where AI can assist in generating prompts, tools, skills, workflows, tests, documentation, and model evaluations.
Develop evaluation frameworks for agentic workflows, including quality, reliability, accuracy, cost, latency, and failure modes.
Use SQL to extract, transform, and analyze data from business and product systems.
Work with Git-based workflows and collaborate with technical teams.
Contribute to AI workflows deployed or supported through GCP, such as BigQuery, Cloud Storage, Vertex AI, or related services.
Experiment with Claude Code, Codex, or similar AI development environments to accelerate AI system development.
Identify opportunities to automate repetitive analytical, operational, and software development tasks using agents.
Communicate technical findings clearly to business, product, and engineering stakeholders.
Bachelor’s degree in Data Science, Statistics, or a related quantitative field, or equivalent practical experience.
Master’s degree in Statistics, Data Science, Artificial Intelligence, Machine Learning, or a related field preferred.
5+ years of professional experience in data science, machine learning, or a closely related quantitative field.
Strong conceptual understanding of statistics, including distributions, uncertainty, hypothesis testing, regression, experimentation, and causal thinking.
Strong conceptual understanding of machine learning, including model evaluation, overfitting, feature engineering, supervised learning, unsupervised learning, and interpretability.
Proficiency with SQL.
Familiarity with Git and collaborative development workflows.
Some understanding of GCP or cloud-based data and AI infrastructure.
Experience working with LLMs, agents, or AI-assisted workflows. 1+ year of hands-on experience in a professional or research setting preferred.
Ability to think critically about AI outputs, limitations, hallucinations, evaluation, and reliability.
Interest in using AI not only as a productivity tool, but as a system-building capability.
This job posting is intended to comply with all applicable laws. If we learn during the course of our recruitment process that, due to an applicant’s location, further information about the position is required, including certain salary information, this information in this posting will be supplemented accordingly.
The estimated base salary range for new hires into this role is $120,000-150,000 annually + bonus depending on factors such as job-related knowledge, relevant experience, and location. We also offer a competitive benefits package, details of which can be found here.
Hybrid: 2 days in office
We are not able to offer sponsorship for this position
Physical Demands