Job Description

Drips – AI Data Analyst

Drips revolutionizes customer engagement with Conversations as a Service (CaaS), delivering scalable, authentic, and data-driven dialogues. As an AI Data Analyst, you will play a critical role in shaping the performance and accuracy of AI-powered conversational systems by analyzing model outputs, refining data pipelines, and ensuring the continuous improvement of AI-driven interactions.

In a world where customer engagement depends on precise, effective AI, Drips differentiates itself by leveraging high-quality data to power meaningful, human-like conversations. Your role will focus on assessing model launch success, curating clean and structured datasets for AI training, and identifying trends to enhance system performance. By applying analytical rigor, strategic problem-solving, and a passion for AI, you will help optimize Drips’ AI models to drive engagement, compliance, and customer satisfaction.

This is an entry-level position that blends data analysis, model evaluation, and cross-functional collaboration to enhance AI effectiveness while maintaining the highest standards of accuracy and compliance.

AI Data Analysis & Intent Modeling

• Analyze AI-powered customer interactions across multiple client use cases and calls to action, ensuring AI models accurately interpret consumer intent.
• Structure and refine training datasets to improve AI decision-making, ensuring the system adapts to real-world language and evolving consumer behaviors.

Model Optimization & Continuous Improvement

• Leverage insights from AI Quality Analysts and other stakeholders to refine AI intent models, response selection, and decision pathways.
• Implement updates to conversational AI based on reported misclassifications, engagement drop-offs, and areas of confusion identified through quality monitoring.
• Work closely with engineering and product teams to test and deploy AI model updates efficiently and accurately.

Data Curation & Annotation

• Create annotation guidelines and frameworks that standardize how AI training data is labeled and utilized.
• Identify gaps or inconsistencies in existing training data, implementing strategies to enhance dataset quality and AI adaptability.

Collaboration & Cross-Team Support

• Work with AI Quality Analysts to interpret findings from conversation audits and translate them into actionable AI model adjustments.
• Partner with product, engineering, and data science teams to refine AI decision-making and conversational flow.

You are a critical thinker with a keen analytical mindset, capable of dissecting complex data to uncover patterns and drive improvements. You thrive in problem-solving environments , where precision and adaptability are key to optimizing AI models. You have a strong attention to detail , ensuring that AI-driven conversations accurately reflect consumer intent across diverse industries and use cases.

You excel at translating data into action , using insights from quality monitoring to refine AI performance and enhance user engagement. You’re comfortable working with large datasets , structuring clean training data, and collaborating across teams to fine-tune AI decision-making. If you enjoy solving challenges, working with cutting-edge AI technology, and making data-driven improvements , this role is for you.

• Bachelor’s degree in Data Science, Analytics, Computer Science, Linguistics, Mathematics, or a related field (or equivalent 1+ years practical experience).
• Strong analytical skills with the ability to interpret data, identify trends, and make data-driven recommendations.
• Basic experience with data manipulation tools such as Excel, SQL, Python, or similar (experience with AI training data is a plus).
• Attention to detail and the ability to recognize patterns and inconsistencies in language, data, and AI model behavior.
• Critical thinking skills to assess AI performance and make informed adjustments based on quality findings.
• Strong communication skills to collaborate with cross-functional teams and translate data insights into actionable improvements.
• Ability to learn and adapt in a fast-paced AI-driven environment with evolving technologies and methodologies.
• Experience with AI models, NLP, or conversational AI (preferred but not required).

Applicant Instructions:

To be considered for the AI Data Analyst position, all applicants must submit a cover letter along with their resume. The cover letter should address the following requirements:

Failure to follow these instructions may result in your application being disqualified. We value attention to detail and clear communication, so make sure your application reflects these qualities!

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