CS2 Trading Analyst – Esports (Odds & Market Performance)

TLDR

Own the analysis of esports markets and match data to improve pricing accuracy and market efficiency while collaborating closely with traders on critical decision-making.

  • Can you spot patterns, anomalies, and inefficiencies in the market with precision?

  • Do you enjoy analysing failures or incidents to improve trading decisions and strengthen automation going forward?

  • Do you like seeing your insights translated into better tools, models, or workflows?

If the answers to the above questions are yes, then this role could be ideal for you!

About the role

Support modelling and trading teams by analysing esports match data and market behaviour to improve odds accuracy and operational decisions, as well as performance monitoring for GRID's esports betting products across multiple titles.

Own the analysis of esports markets and match data to directly improve pricing, market efficiency, and trading performance, with a strong focus on CS2. Work closely with live and pre-match traders to identify anomalies, optimize odds, and support decision-making that impacts P&L across GRID's esports products.

Requirements

What you will do 

  • Analyze esports match data and live market behaviour to improve pricing accuracy and market efficiency

  • Validate and monitor odds models under real trading conditions

  • Identify market patterns, inefficiencies, and anomalies that affect P&L

  • Conduct variance analysis and trading performance reviews

  • Prepare actionable insights and datasets for traders and trading decisions

  • Monitor competitor offerings and identify opportunities to improve trading strategies

  • Support ad-hoc trading or market analysis requests from the trading team

  • Proactively use your esports knowledge to spot where rule changes will impact our models in order to highlight and fix problems before they arise

  • Use your data analysis skills to compare historical outcomes to our current outputs, and identify the extent to which they could negatively impact the business

  • Suggest ways to enhance pricing models via new algorithms and/or improved coding methods, or by investigating with external feed providers where applicable

  • Appraise and test pricing changes to ensure only improvements are released to production

  • Ensure that all processes are documented to a high standard and are ready for both technical and non-technical consumption

  • Have the space to innovate and work on blue-sky research, to help the team be the difference in a competitive marketplace

Your skills will include

  • 3–5 years of experience in a trading, analytics, or quantitative role, ideally within the betting and gaming industry or a comparably fast paced, data rich environment

  • Strong SQL skills are essential; experience with Python, R, or similar tools is a plus

  • Hands-on experience building and maintaining data models in tools like DBT, Databricks, or other modern data stack components

  • Deep understanding of trading fundamentals, including pricing, margin, and risk models

  • Proven ability to independently solve complex problems, applying sound analytical approaches aligned with business goals

  • Experience balancing and delivering against multiple priorities in high-pressure environments

  • Excellent communication skills, with a track record of influencing decisions through insight and data storytelling

  • Collaborative and proactive team player with a growth mindset and high standards for quality

  • Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Economics, Engineering, or Computer Science

Nice to have

  • Interest in competitive gaming and esports ecosystems

  • Bachelor's degree in Mathematics, Statistics, Economics, Data Science, or related field

  • Familiarity with machine learning concepts and applications

GRID eSports develops the GRID Data Platform tailored for the esports and gaming sector, providing detailed in-game and play-by-play data. We support game developers and tournament organizers in maximizing their data assets to boost storytelling, enhance fan engagement, and maintain integrity in the competitive landscape.

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