Job description

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.

Requirements

Must-haves

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
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
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:
Initial interview: 30-minute introductory call, getting to know you
Case interview: 90-minute case discussion, present and debate your skills
Founder interview: 90-minute interview with our CEO, going deep on all topics

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

gomlawsaipythonsql

Platform: ashby
Effort: quick