Data Analyst & QA Specialist
ClarityQ is a well-funded startup which develops a GenAI data analytics platform. It is designed to serve as a true co-pilot for data teams and allow product and business users to interact with the data in natural language, receive answers and gain insights, without overloading the data teams. We harness the power of LLMs to revolutionize the way companies make data-driven decisions, aiming to boost their bottom-line revenue. ClarityQ is led by seasoned entrepreneurs who successfully exited their previous startups and are passionate about building another game-changing product.
A unique hybrid role at the intersection of data, product, and quality assurance. Help ensure ClarityQ delivers accurate, reliable, and insightful answers to our customers while getting hands-on exposure to cutting-edge AI technology from day one.
Key Responsibilities
- Run analyses on customer and internal data to support POCs, customer success, and product decisions.
- Assist in onboarding new customers and running POCs — validating data connections, verifying table, event and semantic catalogs, and making sure every evaluation runs smoothly.
- Test new features and releases across the platform (Dashboards, Context Builder, Slack integration, and more), reproduce and document issues, and verify fixes before they reach customers.
- Own the analytics of ClarityQ itself, using ClarityQ as your daily analytics tool — analyze how customers use our product, uncover insights on usage, engagement, and adoption, and surface findings that shape our product roadmap.
- Leverage advanced AI tools to speed up testing, analysis, and documentation, and continuously find smarter ways to work.
- Work hand-in-hand with our dynamic and fast-paced team, staying aligned on product developments, priorities, and goals.
Requirements
- Tons of motivation: hungry to learn, take ownership, and grow fast.
- Agile: able to switch between analytics and testing quickly, juggle both when needed, and deliver under tight timelines without dropping quality.
- Attention to detail: you notice the small things others miss and don't consider a task done until it's verified.
- Analytical mindset: you enjoy digging into data, asking 'does this make sense?', and getting to the root of a problem.
- Self-starter: you thrive in a fast-paced, unstructured environment and are excited by the challenge of building from scratch.
- Curiosity: genuine interest in AI, data, our product, and the industry we are disrupting.
- People person: great with people and comfortable working directly with customers — listening, communicating clearly in English, and building trust in every interaction.
- Team player: work closely with a small fast-moving team, contributing to a shared vision and collective success.
- Basic SQL knowledge and comfort working with data (academic, bootcamp, or hands-on experience all count).
- Strong analytical and problem-solving skills.
- Excellent written and verbal communication skills in English.
- Comfortable using AI tools as part of your daily workflow, or eager to learn fast.
- Experience with QA, data analysis, BI tools, or data warehouses (Snowflake, BigQuery, Databricks) is an advantage.
- Experience working in an early-stage startup environment is an advantage.