Data Scientist – TV-Insight

Vollzeit

Data Scientist - TV-Insight

Elsbethen, Österreich

Apply now

Are you passionate about creating innovative data-driven products that reshape industries?

TV-Insight is an exciting digital spin-off within Red Bull, located in Elsbethen (Austria), dedicated to revolutionizing the TV measurement and advertisement industry. As a Data Scientist, you will be at the forefront of creating and improving the analytical foundation of our novel product, capable of handling multiple millions of classification tasks every second. Working alongside a team of talented data scientists, data engineers, analysts, and business stakeholders, you will play a key role in defining the success of a state-of-the-art analytics product.

RESPONSIBILITIES

Areas that play to your strengths

All the responsibilities we'll trust you with:

Model Ownership & Production Deployment

You take ownership of the development and deployment of machine learning models for a dedicated TV-Insight market. This includes building and improving real-time machine learning applications as well as developing model components that feed into real-time projection processing. Working closely with a highly specialized team of engineers and data analysts, you ensure a strong understanding of the technical implementation while setting the highest standards for statistical modelling, creating direct business impact from day one.

Exploratory Analysis, Model Understanding & Communication

You conduct thorough exploratory data analyses to evaluate input data and gain a deep understanding of model behaviour and performance. In both research tasks and day-to-day work, you uphold best practices in modelling approaches and production-quality code. You communicate your insights in a clear and accessible way through dashboards and reports, enabling data-driven decision-making for management and key stakeholders.

Continuous Innovation & Technical Excellence

You continuously stay up to date with technological and industry developments to expand your skill set and strengthen your ability to innovate. You critically assess the potential of new methods, tools, and trends, and proactively implement your own ideas in small-scale experiments to test and validate their expected benefits before scaling them into production.

Experience

Your areas of knowledge and expertise

That matter most for this role:

* Master's degree or PhD in a highly quantitative field such as Statistics, Mathematics, Computer Science, or a related discipline
* 3+ years of professional experience in quantitative analytics, data science, or applied statistics.
* Strong hands-on experience in statistical modelling using R or Python, with solid experience working with databases and query languages such as SQL.
* Proven expertise in applying core statistical methods, including regression, classification, and hypothesis testing, to real-world business problems.
* Ability to translate complex analytical results into clear, compelling visualizations and dashboards using tools such as ggplot, R Shiny, or Data Studio.
* Strong presentation and communication skills, with the ability to explain complex technical concepts to non-technical audiences and collaborate effectively in cross-functional teams.
* Travel: 0-10 %

JOIN THE TEAM

Got what it takes?

In your application we want to see your personal style - what makes you tick and why you think your next opportunity is here with us.

Apply now

Due to legal reasons, we are obliged to disclose the minimum salary according to the collective agreement for this position, which is EUR 2.362 gross per month. However, our attractive compensation package is based on market-oriented salaries and is therefore significantly above the stated minimum salary. As an employer, we value diversity and support people in developing their potential and strengths, realizing their ideas and seizing opportunities. We believe passionately that employing a diverse workforce is central to our success. We welcome applications from all members of society irrespective of age, skin colour, religion, gender, sexual orientation or origin.