Back
Metro location and mid-level product-analytics skills increase applicant density despite AI specialization.
Requires product-analytics and AI-tooling familiarity, transferable across tech but somewhat specialized to ad-tech workflows.
Explicit 2–4 years plus mandatory Python, Databricks, AWS, LLM integrations and product-analytics skills enforce strict filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own end-to-end product development for AI-assisted and analytics-heavy workflows, including problem framing, research, analysis, documentation, and execution.
Collaborate with Product Managers and cross-functional teams to define roadmaps, success metrics, prioritize features, and drive adoption through data-driven recommendations.
Design and improve AI-integrated products and workflows that enhance decision quality by integrating structured and unstructured data, APIs, and system integrations with quality control.
2–4 years of experience in product analytics and analytics-driven product development.
Proficiency in Python, and experience working with large-scale data platforms such as Databricks, Spark, and AWS.
Experience with product analytics, experimentation design, APIs, system integrations, and familiarity with AI/LLM tools like OpenAI and Claude APIs.
Bachelor’s or master’s degree in engineering or an MBA.
Experienced in framing ambiguous product problems and driving data-driven, AI-augmented product solutions in cross-functional settings.
Comfortable working with large-scale data environments and integrating AI tools into product workflows and decision processes.
Skilled at stakeholder management across product, data, engineering, and business teams to deliver scalable, analytics-based product features.