Varos
AI Business Analysts to gather requirements and optimize processes
Senior Analytics Engineer
About the role
We're looking for a data guru to build product features and run analyses on top of our massive data set (7,000+ companies first-party data co-op + large public database).
Opportunity to be first 10 employee in a very fast-growing startup that just raised from on of the best VCs in Silicon Valley.
You'll be working lots in SQL, DBT and Python + leveraging LLMs for data enrichment & tagging.
Requirements:
- 6+ years of analytics engineering, data engineering, data science, or other highly analytical, data-oriented roles.
- Excellent communication skills and ability to work with technical and non-technical partners from many teams, especially in exploring decisions and trade-offs
- Advanced proficiency in SQL databases and queries, as well as experience designing data models using dbt
- Working knowledge of Python and cloud-based data warehouse platforms (Snowflake and Athena in particular)
- Commitment to applying software engineering best practices in an analytics setting
- Experience building pipelines for Machine Learning or LLM models and ensuring their reliability using ML/LLM ops techniques
- Startup mentality, solution driven, can do approach
About Varos
AI Business Analysts to gather requirements and optimize processes
Varos AI delivers the work of business analysts 10x faster, better & cheaper with AI agents built for discovery.
Arthur, our AI agent, acts as a Senior Business Analysts and works for you 24/7 in any language. He conducts intelligent 10-15 minutes voice or text-based interviews with your teams to rapidly capture the institutional knowledge you need to execute on projects. He learns from each conversation, cross-references information, and analyzes all the findings to deliver actionable insights.
Arthur is an expert at capturing mapping & optimizing complex processes, gathering knowledge from employees' heads and documenting it, supporting automation projects, uncovering root causes to significant problems and more.
All this information gathered is turned into a private, secure knowledge base that can be used by the org → turning tribal knowledge into institutional knowledge.
For example, Arthur unblocked a critical system migration for a large financial system in 3 days by interviewing 100+ operators in the org, replacing a $1m & 6 month engagement of a consulting firm.
Backed by Y Combinator, Mosaic General Partnership, and leading financial institutions ($8.5m in funding).
