Data Scientist – Decision Support

Role Overview

• Parrot Analytics is the global authority on media and entertainment intelligence, providing the strategic decision support that the world’s leading studios, producers, streamers, investors, and government bodies rely on to de-risk content investment and maximize returns.
• Trusted across the full media economy — from studios and streaming platforms to film funds, sports leagues, and government bodies — Parrot Analytics informs capital allocation, acquisitions, programming strategy, and IP valuation at the highest levels of the industry.
• By measuring the demand and preferences of more than 2 billion audiences worldwide, Parrot Analytics’ AI platform quantifies the value of content, talent, franchises, and sports rights — enabling partners to forecast revenue, assess risk, optimize portfolio strategy, and drive more predictable success.
• This role offers the opportunity to build real technical depth while contributing to meaningful product, platform, and business outcomes.
• Identify patterns, anomalies, and opportunities across large, high-volume datasets to generate actionable insights that drive product, platform, and business decisions.
• Use statistical methods such as hypothesis testing, regression, forecasting, segmentation, experimentation, causal inference, and anomaly detection to solve business problems.
• Partner with platform and data engineering teams to investigate data at scale, validate assumptions, and improve data quality, metric definitions, and analytical datasets.
• Turn open-ended business and platform questions into structured analytical approaches, practical recommendations, and scalable decision-support outputs.
• Develop repeatable analyses, dashboards, prototypes, and workflows that empower both technical and non-technical stakeholders to make better decisions.
• Use SQL and Python and/or R to efficiently query, prepare, analyze, and model data within cloud and distributed environments.
• Apply LLMs and GenAI tools to accelerate coding, exploratory analysis, documentation, prototyping, and insight generation.
• Evaluate and apply analytical, machine learning, and AI-driven approaches where they improve speed, quality, or decision-making impact.
• Present findings through clear storytelling, visualisations, reports, and presentations tailored to diverse audiences.
• Document methods, assumptions, code, and outputs to ensure transparency, reproducibility, and reuse across the team.

Requirements

• Recently completed, a Master’s or PhD in Statistics, Data Science, Mathematics, Computer Science, or a related quantitative discipline.
• Strong foundation in statistical thinking, analytical problem-solving, and data interpretation.
• Proficiency in SQL and working knowledge of Python or R.
• Knowledge in Experimental Design, Design a clean A/B test and Understand model behavior
• Understanding of linear algebra and optimization concepts relevant to machine learning and statistical inference
• Experience with version control (Git) and collaborative development
• Experience preparing, analyzing, and interpreting real-world data.
• Ability to communicate complex analysis clearly and credibly to both technical and non-technical audiences.
• Curiosity, initiative, strong learning agility, and a desire to grow in a fast-moving environment.
• High attention to detail and a practical mindset for balancing rigor with delivery.
• Comfortable working cross-functionally with data scientists, engineers, product teams and business stakeholders.

Tech Stack

• Cloud
• Python
• SQL

Benefits

• You’ll join a team that values strong fundamentals, curiosity, and real-world impact.
• This is an opportunity to build a strong foundation in decision science while working on meaningful problems at the intersection of analytics, platform-scale data, and modern AI-enabled ways of working.
• We are looking for someone who is not only technically capable, but also excited to learn, contribute, and grow into a highly effective data science professional.