Join the Avito team as a "Lead Product Manager, AI/ML Business Insights Product" in Moscow. Work in a strong team, enjoy a flexible schedule, extended VHI (Voluntary Health Insurance), high salaries, career growth, and make a real contribution to the product. We create technologies for millions of users!

About the team: AI Speech Lab is Avito's internal ML product. We analyze thousands of user dialogues to improve sales efficiency and identify growth areas for Avito's products. We are creating the Business Insights platform, which extracts the "voice of the user" from dialogues and digitizes it. The platform helps to quickly understand users' real needs by combining deep qualitative feedback — context and live quotes — with a quantitative assessment of its prevalence. This reduces the time to gain insights for product research from several weeks to 15 minutes.

Examples of future tasks:

• develop a product that helps users independently find answers and conduct research on unstructured data without involving the ML team or analysts;
• build trust in the platform's data among vertical leaders and product teams. Make the tool an integral part of decision-making processes, ensuring transparency and verifiability of insights, for example, through quick access to live quotes;
• expand the product beyond B2B sales calls: integrate text chats, customer support inquiries, and reviews to create a unified omnichannel picture;
• find a balance between the cost of LLM scoring, sample representativeness, and speed to reduce insight waiting time from several hours to 15 minutes.

It would be great if you have:

• 3+ years of experience in DS/ML or Data products and practical experience with LLM applications;
• the ability to work with quantitative and qualitative feedback: systematize fragmented feedback, identify root user problems, and translate them into digitized metrics;
• the ability to work with data: read and verify datasets in SQL, correctly assign tasks to DS/DE, and accept results.

Additionally:

• created self-service tools for analytics or internal data platforms;
• worked with unstructured data: NLP, texts, audio, speech analytics systems, or VoC;
• understand the specifics of the B2B domain, sales processes, or customer service.