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Melotech

Data Scientist

Berlin; New York; LondonRemote · Germany
FullTime · Technology
POSTED 16 SEPT
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Pay · market
€58k–€70k
p25–p75 · n=5
Open for
51d
since 16 Sept
Hiring · 30d
13
0 net · open roles
PythonAWSSQLLLMs

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, Melotech has raised more than $16M from Drive Capital and Europe’s leading VCs: Cherry Ventures, Speedinvest and Global Founders Capital, 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, changing the world of media and entertainment. Being early means every decision you make shapes our trajectory. You're not a cog in the machine but the captain of your own ship, rewarded for performance and respected for leadership. Flat hierarchies mean that your voice matters, your ideas get implemented, and your impact is immediate.

Source · MelotechFirst seen 2 NovOriginal ↗