Senior Product Analyst / Data Scientist

JobgetherAI cloud infrastructure

Workplace type: Remote; based in GermanyFull-TimeSenior

Salary not disclosed

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Job Details

Experience: At least 5 years of professional experience in product analytics, data science, business analytics, or a closely related analytical discipline.
Required Skills: PythonSQLProduct AnalyticsData science

At least 5 years of professional experience in product analytics, data science, business analytics, or a closely related analytical discipline.
Strong proficiency in Python and SQL.
Solid understanding of statistics and methods for interpreting complex datasets.
Hands-on experience analyzing large-scale customer, product, and usage data.
Experience taking analytical projects from business questions through data preparation, analysis, solution development, and production-ready implementation.
Experience defining product and business metrics, building analytical datasets, and establishing reporting frameworks.
Strong commercial and product judgment, balancing customer value, monetization, growth, and profitability.
Practical experience with pricing, packaging, monetization strategies, or commercial analytics.
Ability to turn complex analytical findings into clear recommendations for strategic and operational decisions.
Familiarity with AI-assisted coding tools, including validating their outputs and owning final results.
Familiarity with LLM inference economics, including tokens, throughput, latency, batching, and GPU infrastructure costs, is a plus.

Define, develop, and maintain core product and business metrics and a reliable source of truth.
Analyze self-service customer usage, health, satisfaction, retention risks, needs, and growth opportunities.
Collect, process, and analyze large-scale customer, product, and operational datasets.
Translate customer demand and commercial plans into capacity forecasts.
Monitor capacity utilization and identify opportunities to optimize resource use and commercial value.
Assess and improve pricing and packaging strategies, including capacity and throughput offerings.
Develop data-driven recommendations for customer segmentation, pricing, capacity planning, and monetization.
Own analytical projects from business question definition and data pipelines through statistical analysis and production-ready solutions.
Use Python, SQL, statistical methods, and distributed data-processing tools to develop analytical workflows.
Present actionable findings and collaborate with cross-functional teams to inform product, commercial, and operational decisions.

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