Data Scientist (TV-Insight)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Data Scientist (TV-Insight): Developing and deploying real-time machine learning models for TV measurement and advertisement with an accent on statistical modeling and production-quality code. Focus on building scalable classification applications, conducting exploratory data analysis, and translating complex insights into actionable business dashboards.
Location: Onsite in Elsbethen, Austria
Salary: Minimum €2,362 gross per month (market-oriented compensation significantly above minimum)
is a global brand known for its energy drinks and diverse portfolio of digital products and media ventures.
What you will do
- Take ownership of machine learning model development and deployment for TV-Insight markets.
- Build and improve real-time ML applications and projection processing components.
- Conduct exploratory data analysis to evaluate input data and model behavior.
- Maintain high standards for statistical modeling and production-quality code.
- Communicate analytical insights through clear visualizations and dashboards for stakeholders.
- Continuously innovate by testing new methods and tools in small-scale experiments.
Requirements
- Master’s degree or PhD in Statistics, Mathematics, Computer Science, or a related quantitative field.
- 3+ years of professional experience in data science, quantitative analytics, or applied statistics.
- Strong hands-on experience with Python or R and database query languages like SQL.
- Proven expertise in statistical methods including regression, classification, and hypothesis testing.
- Ability to create compelling visualizations using tools like ggplot, R Shiny, or Data Studio.
- Strong presentation skills to explain technical concepts to non-technical audiences.
Culture & Benefits
- Work within a specialized digital spin-off team focused on cutting-edge analytics.
- Collaborative environment involving data engineers, analysts, and business stakeholders.
- Commitment to diversity and inclusion in the workplace.
- Opportunities for professional development and innovation.
- Market-oriented compensation package.
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