Analytics Engineer, Safety Systems
WFA Digital Insight
The demand for skilled analytics engineers in the AI sector has surged, with a 25% increase in job postings over the past year. As companies like Openai prioritize AI safety, professionals with expertise in data analysis and GTM are in high demand. With its commitment to developing trustworthy AI, Openai stands out as a leader in the field. Before applying, candidates should be aware of the company's hybrid work model and the need for collaboration with cross-functional teams. As the job market continues to evolve, professionals with a strong foundation in data analytics and a passion for AI safety are poised for success.
Job Description
About the Role
The Analytics Engineer role at Openai is a pivotal position that focuses on building a data-centric culture within the Safety Systems team. As an Analytics Engineer, you will be responsible for enhancing decision-making processes and driving strategic initiatives through analytics. Your primary goal will be to develop and maintain canonical data sources and source-of-truth dashboards that provide trustworthy, actionable insights to stakeholders across the organization.The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. As a member of this team, you will collaborate closely with Engineering, Research, and Data Science to advance the company's goals of safe, robust, and reliable AI.
Openai's approach to safety is centered around developing new fundamental solutions to enable the safe deployment of its most advanced models and future AGI. The company's commitment to safety is evident in its dedication to creating a data-centric culture that informs product decisions and company strategy.
What You Will Do
- Design and maintain canonical datasets that serve as sources of truth for safety metrics
- Develop and refine data products, such as dashboards, reports, agent-enabled workflows, and machine-readable interfaces, to empower stakeholders to extract and analyze data independently
- Work closely with stakeholders in Engineering, Research, and Data Science to understand their decision-making needs and design intuitive ways to consume complex safety metrics
- Ensure that analytics and visualizations are both accurate and user-friendly, incorporating user experience principles
- Advocate for data quality, consistency, and reliability across analytics products
- Partner with cross-functional teams to identify and prioritize analytics needs and develop solutions to meet those needs
- Develop and maintain technical documentation for data products and analytics workflows
- Collaborate with researchers and engineers to advance the company's goals of safe, robust, and reliable AI
- Stay up-to-date with industry trends and emerging technologies in data analytics and AI safety
What We Are Looking For
- 5+ years of experience in a relevant data role within dynamic, outcome-driven organizations
- Demonstrated ability to independently own ambiguous, high-impact business problems, from structuring the analytical approach to driving clear recommendations and execution
- Highly autonomous and resourceful, with a track record of navigating data, stakeholder, and operational blockers
- Highly skilled in SQL, with extensive experience extracting large datasets and designing ETL workflows
- Experienced in using business intelligence tools, such as Tableau and Looker, to communicate insights and enable self-serve
- Excellent communication skills, with demonstrated ability to collaborate with researchers, engineers, data scientists, and executives alike
- Best-in-class attention to detail and unwavering commitment to accuracy
- Proven track record of delivering significant business impact, preferably within Finance, Sales, Support, or other GTM domains
- Experience using or building agentic data tools, LLM-powered analytics, or other AI-assisted data workflows
Nice to Have
- Experience in trust and safety, integrity, anti-abuse, or related fields
- Familiarity with advanced custom visualizations, such as Streamlit and Plotly Dash
- Demonstrated prior experience in NLP, large language models, or generative AI
- Experience building data products used by a broad range of stakeholders, from technical practitioners to company leadership
Benefits and Perks
- Competitive salary and equity package
- Opportunity to work with a talented team of researchers, engineers, and data scientists
- Collaborative and dynamic work environment with a hybrid work model
- Professional development opportunities, including training and education programs
- Access to cutting-edge technologies and tools in data analytics and AI safety
- Comprehensive health insurance and benefits package
- Generous paid time off and holiday policy
- Remote work stipend and support for remote work setup
- Opportunity to contribute to the development of safe and reliable AI systems
How to Stand Out
- When applying, be sure to highlight your experience with GTM and Excel, as well as your ability to work with large datasets and design ETL workflows.
- Showcase your skills in data visualization and communication, including experience with business intelligence tools like Tableau and Looker.
- Prepare to discuss your experience with data quality, consistency, and reliability, as well as your ability to advocate for these principles in an analytics role.
- Be ready to talk about your experience working with cross-functional teams, including researchers, engineers, and data scientists.
- When interviewing, ask about the company's approach to safety and how the Analytics Engineer role contributes to this effort.
- Consider sharing examples of your experience with agentic data tools, LLM-powered analytics, or other AI-assisted data workflows.
- Be prepared to discuss your experience with SQL and data modeling, as well as your ability to design and maintain canonical datasets.
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