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Melotech is a media and entertainment company using technology to create content at scale. Founded by entrepreneur Soheil Mirpour and backed by top-tier VCs (Cherry Ventures, Speedinvest, GFC) and angels from Spotify, Blackstone, and KKR, the company has achieved 3 billion minutes of consumption in 24 months.
You will be Melotech's first dedicated Data Scientist, working autonomously alongside the founder and a backend engineer who manages infrastructure. Your focus is extracting insights from complex data sources to answer critical business questions: What cultural trends are emerging? How can we predict virality? What categories are underserved?
Key responsibilities include:
- Discovering and acquiring untapped data sources using creative scraping and acquisition techniques beyond standard APIs
- Analyzing trends, audience behavior, and performance across streaming and social platforms to identify growth opportunities
- Prototyping and deploying ML models on AWS for virality prediction and content analysis, validating performance in production
- Designing and interpreting A/B tests, holdouts, and spend experiments to guide resource allocation
- Owning dashboards and reports that leadership relies on; investigating metric movements and root causes
- Leveraging LLMs and agentic coding tools to accelerate data cleaning, analysis, and reporting
You will work in a flat hierarchy with early-stage impact: every decision shapes company trajectory. The team meets globally for offsites but operates remotely otherwise. Compensation includes competitive salary and equity ownership.
REQUIREMENTS:
- Degree in Data Science, Statistics, Computer Science, Physics, Math, or related quantitative field
- 3+ years of hands-on data science in fast-paced environments (Tier 1 consultancies, Big Tech, high-growth startups, or media industry leaders)
- Expert-level Python proficiency with standard data science and ML frameworks; SQL as a daily tool
- Demonstrated experience scraping and acquiring raw data from new sources with creative solutions
- Strong statistical rigor: design and interpret experiments properly, distinguish signal from noise, run A/B tests or causal analyses that influenced decisions
- Track record of deploying models in production and maintaining their integrity over time
- Extensive hands-on experience with agentic coding tools and LLMs in data workflows
- Ability to translate data insights into business decisions and create trusted dashboards/visualizations (standard libraries or Tableau)
- Strong collaboration skills across engineering, product, and business teams; described as hard-working, ambitious, and persistent
- Thrives in fast-paced, performance-oriented environments
- Plus: passion for music, video, or social media
