GRID esports

MOBA Trading Analyst – Esports (m/f/x)

GRID esports  •  Remote  •  18 hours ago
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Job Description

  • Can you identify pricing inefficiencies in MOBA markets by combining game knowledge with data analysis?

  • Do you thrive on turning messy match data into actionable insights that improve odds models?

  • Are you passionate about Dota 2 and the growing Honor of Kings competitive scene?

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

About the role

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

Support the analysis of MOBA markets and match data to directly improve pricing, market efficiency, and trading performance. Work closely with live and pre-match traders on MOBA titles to identify anomalies, optimise odds, and support decision-making that impacts P&L across GRID's MOBA product lines.

Requirements

What you will do

  • Analyse MOBA matches behaviour to improve pricing accuracy and market efficiency

  • Conduct variance analysis and trading performance reviews

  • Validate and monitor odds models for MOBA titles under real trading conditions

  • Detect model drift, pricing inefficiencies, and performance anomalies impacting P&L

  • Prepare actionable insights for traders and trading decision-making

  • Monitor competitor offerings and identify opportunities to improve trading strategies

  • Analyse MOBA match outcomes, meta shifts, patch changes, and gameplay trends

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

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

  • Translate analytical findings into clear, compelling narratives for both technical and non-technical audiences.

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

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

Your skills will include

  • 3+ years experience in sports betting, trading, or quantitative analysis

  • Statistical modelling and skills in data analytics

  • Deep understanding of Dota 2: hero mechanics, item builds, tournament formats

  • Good knowledge of LoL,including match dynamics, maps, and player behaviour

  • Solid understanding of trading fundamentals: pricing, margin, overround, and risk models

  • Strong attention to detail and ability to retain information

  • Strong statistical, mathematical, and analytical skills with practical application to pricing and risk

  • Positive ‘can do’ attitude, and ability to meet deadlines

  • Willingness to learn and adapt to new environments

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

  • SQL skills or experience with Python, R, or similar tools is a plus

GRID esports

About GRID esports

GRID unlocks the power of official live esports data, fueling next-generation betting, media, and competitive gaming experiences. Through exclusive partnerships with top game publishers and tournament organizers—including Riot Games, BLAST, KRAFTON, and Ubisoft—GRID delivers real-time, high-integrity data and live streaming straight from the source. Its proprietary in-game data infrastructure powers the industry’s most secure, scalable, and engaging products, helping operators, teams, and tournament organizers stay ahead while keeping fans engaged. With a relentless focus on innovation and integrity, GRID is shaping the future of esports by unlocking the full potential of official data for everyone.

Industry
IT & Software
Company Size
51-200 employees
Headquarters
Berlin, DE
Year Founded
2018
Website
grid.gg
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