Market Maker
Manages liquidity, spreads, execution, inventory, hedging, exchange connectivity, and risk so markets can absorb orders without uncontrolled exposure.
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Also listed as
Quant Trader · Algorithmic Trader · Liquidity Provider
What this role actually does
This is hands-on work. The role may need to monitor markets and systems, adjust parameters within limits, review fills, and manage exposure.
The boundary matters: it owns liquidity provision, pricing and execution, and inventory risk, not promising token price and protocol marketing.
Where the role sits
Market Maker usually sits inside Trading, Markets, Treasury, Risk, or quantitative engineering teams. Common reporting lines include Head of Trading, Head of Markets, Chief Investment Officer, or Risk Lead. Usually a specialized full-time role, although liquidity provision may also be delivered by external market-making firms under commercial agreements. The role usually collaborates with DeFi Analyst, Tokenomics Analyst, Backend Engineer, Protocol Researcher.
Core responsibilities
- Monitor order books, AMMs, spreads, depth, volume, volatility, fees, and inventory
- Design or operate pricing and execution strategies
- Manage hedging, exposure, venue limits, and adverse selection
- Maintain exchange, custody, API, and monitoring infrastructure
- Review execution quality and market conditions
- Escalate when models, venues, custody, or risk limits fail
Daily, weekly, and reactive work
A typical day
Monitor markets and systems, adjust parameters within limits, review fills, and manage exposure.
Weekly or monthly
Analyse execution, stress-test assumptions, review venue risk, and update strategy or limits.
When conditions change
Respond to extreme volatility, exchange outage, API failure, oracle issue, depeg, custody event, or a model behaving outside expected conditions.
Deliverables
How success is judged
- Stable execution within mandate
- Controlled inventory risk
- Appropriate spreads and depth
- System reliability
- Clear limit compliance
Read signals in context. Read stable execution within mandate together with controlled inventory risk. Neither signal is meaningful without the relevant launch, incident, market, workload, or attribution context.
Tools in practice
- Python or C++
- Research market behaviour, test pricing or hedging logic, and review execution and risk under defined scenarios.
- exchange APIs
- Stream order-book and trade data, submit or cancel orders, manage rate limits, and detect venue or connection failures.
- market data
- Build a consistent view of prices, depth, volatility, fees, funding, and liquidity across venues.
- risk systems
- Enforce inventory, exposure, loss, venue, and counterparty limits and trigger escalation when a strategy breaches them.
- Grafana
- Monitor health, latency, errors, resource use, and alert thresholds, then connect incidents to recovery and prevention work.
- spreadsheets and databases
- Structure the records behind liquidity report and spread and depth analysis and make review status visible.
Skills and prerequisite knowledge
Hard skills
- Market microstructure
- Statistics
- Algorithmic execution
- Risk management
- Systems and data engineering
Working skills
- Risk discipline
- Decision-making under uncertainty
- Clear escalation
- Numerical skepticism
- Ability to separate performance from luck
Prerequisite knowledge
Know order books, AMMs, fees, slippage, adverse selection, hedging, venue risk, custody, and the mandate's legal and commercial constraints.
Expectations by level
Entry level
At entry level, a candidate should be able to complete a scoped assignment with review. That includes the ability to monitor order books, AMMs, spreads, depth, volume, volatility, fees, and inventory, to design or operate pricing and execution strategies, and to produce reviewable artifacts such as a liquidity report and spread and depth analysis.
Mid level
At mid level, the practitioner normally owns liquidity provision, pricing and execution, and inventory risk without constant supervision. They can coordinate adjacent teams and improve the workflow behind a liquidity report and spread and depth analysis, including when the role must respond to extreme volatility, exchange outage, API failure, oracle issue, depeg, custody event, or a model behaving outside expected conditions.
Senior
At senior level, the work shifts toward standards, decision rights, and review quality. A senior Market Maker defines how liquidity provision, pricing and execution, and inventory risk are handled, reviews high-risk cases, and builds systems that do not depend on one person.
Proof of work and portfolio
Reviewers should be able to inspect a liquidity report and spread and depth analysis, trace the inputs or decisions behind the work, and understand what the candidate personally owned.
Strong proof
- A spread and inventory simulation
- An execution-quality analysis
- A risk dashboard
- A market incident postmortem
Weak evidence
- Backtests with no fees or latency
- Profit screenshots
- Strategies that assume unlimited liquidity or no risk limits
Common mistakes and misconceptions
- Taking responsibility for promising token price and protocol marketing without the mandate or approval to do so
Common misconception
Market Maker may overlap with DeFi Analyst, but the hiring evidence is different. This role is judged on liquidity provision, pricing and execution, and inventory risk, not on ownership of promising token price and protocol marketing.
Scope boundaries
Usually owns
- Liquidity provision
- Pricing and execution
- Inventory risk
- Exchange and venue operations
- Monitoring
- Risk limits
Usually does not own
- Promising token price
- Protocol marketing
- Treasury strategy generally
- Exchange listing decisions
- Uncontrolled proprietary risk
Interview focus
Expect questions about market microstructure, statistics, and algorithmic execution, plus a scenario where the role must respond to extreme volatility, exchange outage, API failure, oracle issue, depeg, custody event, or a model behaving outside expected conditions. Interviewers are looking for evidence that the candidate knows where liquidity provision and pricing and execution stop and promising token price and protocol marketing begin.
How should spreads change with volatility and inventory?
What makes apparent liquidity unreliable?
How would you respond when an exchange connection fails during a fast market?
Compensation and role risks
Compensation may combine salary and performance bonus, while external market-making firms use commercial agreements. Broad finance ranges are not direct role evidence.
No reliable role-specific range
KRAFT did not find a reliable role-specific range that meets the evidence standard. Compensation may still exist through salary, contract fees, retainers, grants, commissions, token or equity packages, creator revenue, or business economics. These models are described separately rather than compressed into an invented number.
Wider Web3 market, for scale
Typical advertised averages $65,000 – $200,000 / year
Individual postings run from about $40,000 to $350,000.
Across the role categories this index tracks, advertised averages sit between roughly $65,000 and $200,000 per year, with individual postings from about $40,000 to $350,000. This is whole-market scale from advertised roles - not a figure for this specific role, and not verified paid compensation.
Role risks
- Performance and model risk
- Venue and custody failure
- Bonus-driven incentives
- Extreme market events
- Regulatory and counterparty exposure
Compensation can change materially by geography, seniority, employment model, company stage, market cycle, and the mix of cash, bonus, commission, equity, token, vesting, royalties, or fees. A published range is useful only when those dimensions match the role being considered.
How to read compensation evidence
- Direct
- Evidence from the same or a materially equivalent role.
- Adjacent
- Evidence from a neighbouring occupation, used only for context.
- Broad market
- Category-level Web3 or labour-market evidence.
- Unverified
- Estimates without enough source or methodology detail.
Confidence reflects the quality and comparability of the evidence, not the value or legitimacy of the role.
Career path and role fit
Common progression
May fit people who
People with strong quantitative, systems, and risk discipline who can distinguish a profitable period from a robust process.
May not fit people who
People attracted mainly by trading upside or uncomfortable with strict limits and operational controls.
Practical next steps
How this guide is built. Role content is drawn from current first-party hiring material and reputable industry evidence, with compensation labelled by confidence and evidence tier rather than a single number.
Turn this role into evidence.
Choose a proof-of-work project, package the result, and practice the questions this role is likely to ask.