Senior Data Scientist - Detection & Modeling

TWG Global AI; New York (NY); On-site; USD 190,000 - 290,000; Full time

Benefits offered by this job

Medical benefits

Bonus opportunity

Onsite work

Job summary

TWG AI is seeking a Senior Data Scientist for Detection & Modeling to own features and models at the core of surveillance systems, turning raw trading behavior into scored, explainable signals and evolving that layer as datasets grow.

Based in Santa Monica, CA or New York, NY, this onsite role combines hands-on modeling with scalable design across two detection stacks and venues, while collaborating with teams to enhance labeling and calibration. A base pay range and full benefits are provided.

Qualifications

• Strong feature engineering and applied ML on transactional or time-series data.
• Hands-on anomaly detection using unsupervised methods.
• Solid statistics, calibration, and dealing with imperfect labels.
• Production ML: deployment, monitoring, and maintenance.
• Scalable modeling across detectors, venues, and market types.
• Fraud, risk, or market-surveillance experience is a plus.
• FIX / market microstructure fluency and on-chain data familiarity are a plus.

Responsibilities

• Design and refine features on large-scale financial time-series and on-chain data, with emphasis on signals that hold up under noisy, heavy-tailed conditions
• Develop and improve anomaly-detection models across both supervised and unsupervised approaches
• Evolve the model architectures as labels accumulate — from simpler classifiers toward multi-class, per-scenario, and ensemble designs
• Improve detector calibration so scores are trustworthy and comparable across market types and venues
• Partner with the validation and analyst teams on the labeling pipelines that supply the models' training signal

Skills

Feature engineering

Time-series ML

Anomaly detection

Unsupervised methods

Model calibration

Production ML

Fraud risk domain

On-chain data familiarity

FIX / market microstructure

Job description

The Organization

At TWG AI, we drive innovation and business transformation across a range of industries—including financial services, insurance, technology, media, and sports—by leveraging data and AI as core assets. Our AI-first, cloud-native approach delivers real-time intelligence and interactive business applications, empowering informed decision-making for both customers and employees.

We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game-changing efforts in marketing, operations, and product development.

You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data-driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation.

At TWG, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses.

The Role

As a Senior Data Scientist for Detection & Modeling, you'll own the features and models at the core of the surveillance systems — the layer that turns raw trading behavior into scored, explainable signals — and you'll evolve that layer as the systems mature and the labeled datasets grow. The work now spans two detection stacks on different grains: the account-grain L1–L3 stack on the US exchange and the wallet/cluster-grain D1–D3 stack of the DeFi Integrity Engine. The two seats split by venue focus while operating as one modeling practice: shared methodology (robust statistics on heavy-tailed data, calibration discipline, the labeling loop), different substrates. This is a hands-on modeling role with a lot of room to shape the detection architecture over the life of the program.

Key Responsibilities:

• Design and refine features on large-scale financial time-series and on-chain data, with an emphasis on signals that hold up under noisy, heavy-tailed conditions
• Develop and improve anomaly-detection models across both supervised and unsupervised approaches
• Evolve the model architectures as labels accumulate — from simpler classifiers toward multi-class, per-scenario, and ensemble designs; on the DeFi side, activate the supervised layer from a standing start as the first disposition labels arrive
• Improve detector calibration so scores are trustworthy and comparable across market types and venues
• Partner with the validation and analyst teams on the labeling pipelines that supply the models' training signal

Qualifications:

• Strong feature engineering and applied ML on transactional or time-series data
• Hands-on experience with anomaly detection and unsupervised methods (e.g., isolation forests, density-based methods, autoencoders)
• Solid statistical foundations, including model calibration and working with imperfect labels
• Production ML experience — you ship, monitor, and maintain models over time
• Comfort scaling a modeling approach across many detectors, market types, and venues, rather than building one-off models
• Fraud, risk, integrity, or market-surveillance domain experience a plus
• FIX / market-microstructure fluency a plus; on-chain data familiarity a plus

Position Location:

This is an onsite position based out of our Santa Monica, CA or New York, NY offices.

Compensation:

The base pay for this position is $190,000-290,000. A bonus will be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits.

TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.