Data Scientist

Posted One Month Ago
3 Locations
In-Office or Remote
Mid level
Artificial Intelligence • Digital Media • Music • News + Entertainment • Software
WE CREATE ART AND APPLICATIONS FOR HUMANS TO ENJOY.
The Role
The Data Scientist will turn messy media and audience data into business insights and decisions. Responsibilities include sourcing and cleaning data, analyzing trends and audience behavior, designing experiments, building and deploying forecasting and content-analysis models on AWS, maintaining trusted dashboards and reports, and applying LLMs and agentic coding tools. The role works autonomously with engineering, product, business, and company leadership in a fast-paced remote startup environment.
Summary Generated by Built In

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.

We pay competitive salaries and make you an owner of the business with equity. We work remotely to give you complete freedom over your life, while meeting regularly around the world for global offsites where we strategize, bond, and push boundaries together.

 

What the process will look like

We hire on a rolling basis. Earliest starting date is always ASAP.

Once you begin our process, you can progress from start to offer within a week, depending on how quickly you can move through each stage:

  1. Initial interview: 30-minute introductory call, getting to know you

  2. Case interview: 90-minute case discussion, present and debate your skills

  3. Founder interview: 90-minute interview with our CEO, going deep on all topics

  4. Offer, contract signing and onboarding

Note: As we are still in stealth, you will learn more about Melotech as you progress through the stages. By the end of the Founder interview, you will have a full grasp of our business and the details of your role.

 

Skills Required

  • Degree in Data Science, Statistics, Computer Science, Physics, Math, or a related quantitative field
  • At least 3 years of hands-on data science experience in a fast-paced business environment
  • Expert-level Python proficiency with standard data science and machine learning frameworks
  • Daily SQL proficiency
  • Experience bringing new raw data sources into reliable use
  • Strong statistical rigor, including designing and interpreting experiments, A/B tests, or causal analyses
  • Experience deploying production machine learning models and maintaining model reliability over time
  • Extensive hands-on experience with agentic coding tools and LLMs in data workflows
  • Ability to translate data and statistical findings into business decisions and recommended actions
  • Experience building trusted dashboards and visualizations using standard libraries or Tableau
  • Ability to collaborate across engineering, product, and business teams
  • Ability to thrive in a fast-paced, performance-oriented environment
  • Strong interest in music, video, or social media
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The Company
HQ: Berlin
1 Employee

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