Senior Data Scientist

About the role

The will own the end to end analytics that underpin our most critical institutional relationships with market makers, large takers, and brokerages that drive a disproportionate share of platform volume. You will be the internal authority who understands how each counterparty trades, how they monetize their activity with us, and whether the health of these relationships is strengthening or eroding over time. This role requires you to move fluidly between rigorous analysis of order level flow and commercial conversations that explain what the numbers mean for partnership terms and strategic decisions. You will operate in a fast moving environment where the institutional side of the business is being built as you go, requiring both judgment and adaptability. A core part of the role will involve quantifying how institutional flow changes market liquidity, spreads, and the experience of retail traders on the opposite side of the market. You will partner closely with analytics engineers to transform recurring relationship reporting into modeled datasets and reusable logic, ensuring that account reviews do not start from scratch each quarter. Another key ownership will be documenting your work end to end so clearly that any teammate can pick up your analysis and use it without friction or additional explanation.

Key facts

What you'll do

Own the analytics on our largest makers, takers, and brokerages, and be the internal source of truth on how each relationship is performing across volume, concentration, and profitability dimensions.

Build the account level view of every major counterparty, including volume trends, flow composition, spread capture, fee and rebate economics, and multi period trend analysis to support strategic decisions.

Monitor counterparty health continuously and surface concentration risk, deteriorating engagement, or churn signals early enough for the business teams to take timely action.

Analyze trading behavior to understand how each professional participant actually makes money on our platform, evaluating whether the terms we have extended still align with their economics and our risk profile.

Support the institutional team during reviews and negotiations by providing analysis that clarifies what a counterparty is worth, what they are requesting, and what we should be willing to offer.

Quantify how institutional flow affects the broader market, including impacts on liquidity, spreads, and the quality of experience for retail traders positioned on the other side of those trades.

Work with analytics engineers to turn ad hoc relationship reporting into modeled datasets and stable pipelines, reducing manual effort and enabling scalable analysis over time.

Own documentation end to end, writing clearly and thoroughly enough that any teammate can understand, reuse, and build upon your analysis without friction or additional context.

Requirements

7+ years in analytics, trading, or counterparty analysis, ideally at an exchange, trading venue, brokerage, or market making firm where you have evaluated relationships and risk at scale.

Expert SQL capability, with the ability to work directly against order book and transaction level data without supervision, writing efficient, maintainable queries that support high stakes decisions.

Deep understanding of how professional market participants make money, including concepts such as spread capture, adverse selection, inventory risk, and the economics of providing liquidity in competitive markets.

Credibility in technical conversations with sophisticated counterparties, including firms that have their own quants and data teams, where you must hold your own by demonstrating rigor and insight.

Commercial instinct that allows you to look at a relationship and quickly articulate what it is worth to us, where the leverage exists, and how changes in terms may affect behavior and profitability over time.

Strong communication and discretion, especially when handling sensitive counterparty information and when presenting findings and recommendations in front of external partners and internal leadership.

Comfortable operating in a fast moving environment where business logic, fee structures, and eligibility rules change frequently, requiring rapid learning and precise execution under tight timelines.

Nice to have

Experience with institutional pricing, tiered fee programs, and structured rebate design, which can help you recommend terms that align incentives and improve long term relationship health.

Familiarity with on chain data or blockchain analytics, enabling you to work directly with transparent, immutable ledgers when analyzing flows that originate or settle through crypto networks.

Python or R skills for deeper statistical work on trading behavior, including modeling, experimentation, and advanced analysis that cannot be performed directly in SQL.

Prior experience in fintech, crypto, prediction markets, or other data intensive financial products, where domain specific nuances materially improve the speed and accuracy of your contributions.

Practical notes

The role is full time based in New York, and candidates must be able to work from our office location as required by the position.

Travel is not expected as part of the standard work arrangement for this role.

This role is not eligible for visa sponsorship at this time, and successful candidates must already have the right to work in the United States.

Applications will be reviewed on a rolling basis, so early submission is encouraged to ensure full consideration and timely feedback during the hiring process.