Data Scientist

Melotech•Berlin, NY

7d•Remote

About The Position

Join us as our first dedicated Data Scientist to bring order to the chaos of culture. You'll extract insights from hard-to-reach data sources to tackle the big questions: What cultural trends are emerging that everyone else is missing? How can we predict virality? And what characterizes an underserved category? 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.

Requirements

A degree in Data Science, Statistics, Computer Science, Physics, Math or a related quantitative field
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
Expert-level proficiency with the standard data science and ML frameworks in Python
SQL as a daily tool
Experience scraping and acquiring raw data from new sources, building creative solutions to reach datasets beyond standard APIs
Ability to design and read experiments properly, know when a signal is noise, and have run A/B tests or causal analyses that changed a decision
Experience deploying models that people actually used, and knowing what it takes to keep them honest over time
Extensive hands-on experience with agentic coding tools and LLMs in your data workflows
Ability to find the opportunity in the data and propose the next step
Ability to create dashboards and visualizations (standard libraries or Tableau) that leadership trusts
Ability to work well across engineering, product and business teams
Thrive in a fast-paced and performance-oriented environment

Nice To Haves

Obsessed with music, video or social media

Responsibilities

Discovering and opening up untapped sources, with creative scraping and acquisition techniques when standard APIs run out
Analyzing trends, audience behavior and performance across streaming and social to find the underserved categories and the next growth opportunity, and proposing the next step
Prototyping and deploying ML models on AWS for virality prediction and content analysis, and checking whether they hold up in production
Designing and reading A/B tests, holdouts and spend experiments across our releases and campaigns, and telling the team where the next dollar should go
Owning the dashboards and reports leadership runs on, and investigating what really drives a metric when it moves
Using LLMs and agentic coding tools to accelerate data cleaning, analysis and reporting