Skills this job asks for
PlumbingMachine learningAWSBudgetingLeadershipLLMsStatisticsPythonSQLTableauSocial media
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Sponsorship verdict
No sponsorship evidence yet
No government record and no wording either way. Not a refusal: ask the recruiter.
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No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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Can’t check pay against the visa rulesNo salary stated. Germany EU Blue Card needs at least €50,700 a year (shortage-occupation / recent-graduate: €45,934).
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Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Can’t check pay against the visa rules
- No salary stated. Germany EU Blue Card needs at least €50,700 a year (shortage-occupation / recent-graduate: €45,934). Source: https://www.make-it-in-germany.com/en/visa-residence/types/eu-blue-card, rules effective 2026-01-01.
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Before you apply
Sponsorship unknown
No register record and no sponsorship wording in the posting. Worth asking the employer before investing significant time.
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About the role
Who we are
Melotech is revolutionizing media and entertainment. We create art through technology for humans to enjoy. In just 24 months, our work has been heard, watched and loved for over 4 billion minutes worldwide.
Founded by entrepreneur and investor Soheil Mirpour, we are backed by top VCs Cherry Ventures, Speedinvest and GFC, alongside world-class angels from firms such as Spotify, Blackstone and KKR.
What you will do
Join us as our first dedicated Data Scientist to bring order to the chaos of culture. You'll turn raw, messy data into insights to tackle the big questions: What is changing in how people find and enjoy media? Why do some bets work and others not? And where is our next opportunity? We sit on a lot of data we do not use yet, and you are the person who turns it into decisions. You work fully autonomously alongside our founder and the team, next to a backend engineer who owns the pipelines and infrastructure, so your time goes into the questions rather than the plumbing. We will walk you through exactly what we are building as you go through the process. On a typical day, your tasks may include:
• New data sources: finding and opening up new sources that help us make better decisions
• Trends and audiences: analyzing trends, audience behavior and performance to find the next growth opportunity, and proposing the next step
• Prediction: prototyping and deploying ML models on AWS for forecasting and content analysis, and checking whether they hold up in production
• Experiments: designing and reading A/B tests, holdouts and spend experiments across our products and campaigns, and telling the team where the next dollar should go
• Numbers people trust: owning the dashboards and reports leadership runs on, and investigating what really drives a metric when it moves
• AI-native workflows: using LLMs and agentic coding tools to accelerate data cleaning, analysis and reporting
Who you are
We look for battle-tested data scientists who understand that real impact comes from turning messy, unstructured data into business-critical insights that drive company direction. You don't just build models: you solve business problems and translate statistical findings into actions the team takes.
Typically, your profile will look like this:
• Background: a degree in Data Science, Statistics, Computer Science, Physics, Math or a related quantitative field
• Experience: 3 or more years of hands-on data science in fast-paced business environments, at Tier 1 consultancies, Big Tech, high-growth start-ups and scale-ups, or media industry leaders
• Python: expert-level proficiency with the standard data science and ML frameworks, and SQL as a daily tool
• Data acquisition: you have brought new raw data sources into use and made them reliable enough to decide on
• Statistical rigour: you design and read experiments properly, you know when a signal is noise, and you have run A/B tests or causal analyses that changed a decision
• Models in production: you have deployed models that people actually used, and you know what it takes to keep them honest over time
• AI-native: extensive hands-on experience with agentic coding tools and LLMs in your data workflows
• From data to decision: you find the opportunity in the data and propose the next step, and your dashboards and visualizations (standard libraries or Tableau) are the ones leadership trusts
• Collaboration: you work well across engineering, product and business teams, and colleagues would describe you as hard-working, ambitious and persistent
• Pace: you thrive in a fast-paced and performance-oriented environment
• A big plus: you're obsessed with music, video or social media
What makes this exciting
You are one of the first employees of an ambitious team, changin
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