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Algorithmic Execution Quant Jobs in Seattle, WA (NOW HIRING)

Apply machine learning, graph and network algorithms, anomaly detection, and other quantitative ... execution, combining ML models, heuristics, feedback loops, and human-in-the-loop review where ...

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Senior Applied Scientist, Trust & Safety

Seattle, WA · On-site

$104K - $142K/yr

Apply machine learning, graph and network algorithms, anomaly detection, and other quantitative ... execution, combining ML models, heuristics, feedback loops, and human-in-the-loop review where ...

You will lead Strategy and Execution of a technical roadmap that will increase the velocity of ... data structures and algorithms * Experience solving analytical problems with quantitative ...

You will lead Strategy and Execution of a technical roadmap that will increase the velocity of ... data structures and algorithms * Experience solving analytical problems with quantitative ...

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Algorithmic Execution Quant information

See Seattle, WA salary details

$59.7K

$135.6K

$223.6K

How much do algorithmic execution quant jobs pay per year?

As of Jun 12, 2026, the average yearly pay for algorithmic execution quant in Seattle, WA is $135,613.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,300.00 and $173,500.00 per year, depending on experience, location, and employer.

What is the difference between Algorithmic Execution Quant vs Quantitative Trader?

AspectAlgorithmic Execution QuantQuantitative Trader
Primary FocusDeveloping and implementing algorithms for trade execution to minimize market impactCreating trading strategies to generate alpha and profit from market movements
Work EnvironmentQuantitative research teams, trading desks, technology-drivenTrading floors, portfolio management teams, research departments
Required SkillsProgramming, market microstructure, execution algorithmsQuantitative modeling, market analysis, strategy development

While both roles involve quantitative skills, an Algorithmic Execution Quant specializes in optimizing trade execution processes, whereas a Quantitative Trader focuses on developing strategies to generate profits. The roles often collaborate but serve different functions within trading firms.

What jobs pay 2000 a day?

Algorithmic Execution Quants working in finance or trading firms can sometimes earn $2,000 or more per day through high-frequency trading, proprietary trading, or managing large portfolios. These roles typically require advanced quantitative skills, programming expertise, and experience with trading platforms and financial models.

What are the key skills and qualifications needed to thrive as an Algorithmic Execution Quant, and why are they important?

To thrive as an Algorithmic Execution Quant, you need a strong background in quantitative analysis, programming (often in Python or C++), and a solid understanding of financial markets, typically supported by an advanced degree in a quantitative discipline. Proficiency with statistical modeling tools, trading platforms, and market data systems, as well as familiarity with technologies like FIX protocol, is crucial. Strong problem-solving ability, attention to detail, and effective communication help you collaborate across trading, research, and technology teams. These skills are essential for designing, optimizing, and maintaining robust trading algorithms that achieve best execution and mitigate risk in fast-moving markets.

How much do algorithmic quants make?

Algorithmic execution quants typically earn between $100,000 and $200,000 annually at entry-level, with experienced professionals earning over $300,000 including bonuses. Compensation varies based on experience, firm size, location, and performance, and often includes bonuses tied to trading profits and technical skills in programming and quantitative analysis.

Is 40 too old to become an algorithmic execution quant?

Age is not a strict barrier to becoming an algorithmic execution quant, as the role values skills in programming, quantitative analysis, and financial markets. Many professionals transition into quant roles later in their careers by acquiring relevant knowledge through advanced degrees, certifications, or self-study. Success depends on your technical skills, experience, and ability to adapt to a fast-paced, data-driven environment.

What are some common challenges faced by Algorithmic Execution Quants when developing and deploying trading algorithms?

Algorithmic Execution Quants often encounter challenges such as adapting strategies to rapidly changing market conditions, managing latency and slippage, and ensuring compliance with regulatory requirements. They must also balance the need for innovation with the necessity for robust risk controls and system reliability. Collaboration with traders, developers, and risk managers is essential to refine algorithms and ensure they perform optimally in live trading environments.

Do JP Morgan hire quants?

Yes, JP Morgan hires quantitative analysts and algorithmic execution quants who develop trading algorithms, optimize execution strategies, and analyze market data. These roles typically require strong programming skills, knowledge of financial markets, and experience with quantitative modeling tools. JP Morgan is known for employing quants across its trading and risk management divisions.

What does an Algorithmic Execution Quant do?

An Algorithmic Execution Quant is responsible for designing, developing, and optimizing algorithms that execute large financial trades efficiently and at minimal cost. They analyze market microstructure, create models to predict market impact, and work closely with traders and engineers to implement these strategies in real-time trading systems. Their work is essential in minimizing transaction costs and improving trade execution quality for their firm.
What job categories do people searching Algorithmic Execution Quant jobs in Seattle, WA look for? The top searched job categories for Algorithmic Execution Quant jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Algorithmic Execution Quant jobs? Cities near Seattle, WA with the most Algorithmic Execution Quant job openings:
Senior Applied Scientist, Trust & Safety

Senior Applied Scientist, Trust & Safety

DAT

Seattle, WA

$104K - $142K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago


Job description

About DAT

DAT Freight & Analytics is an award-winning employer of choice and a next-generation SaaS technology company that has been at the leading edge of freight and logistics innovation for nearly five decades. Founded in 1978, DAT operates the largest freight marketplace in North America - processing 250 million+ load posts annually and maintaining one of the largest repositories of freight market transaction data in the world. On a defined path to $1 billion in revenue, DAT deploys a suite of software solutions, machine learning models, and intelligent automation tools that help brokers, carriers, and shippers price freight accurately, source capacity, reduce risk, and operate more efficiently. With nearly 700 teammates across offices in Denver, CO; Portland, OR; Seattle, WA; Springfield, MO; Toronto, ON; and Bangalore, India, DAT combines the credibility of a multi-decade market leader with the drive of a company that is not done disrupting the industry it helped build. For more information, visit www.DAT.com

Job Application Deadline: 06/30/2026

The Opportunity

DAT's Trust and Safety Science team is seeking a Senior Applied Scientist to design and deploy the next generation of risk models and intelligent decision systems that help detect, prevent, and mitigate unsafe, fraudulent, or otherwise harmful behavior across our network. This role sits at the intersection of machine learning, risk decisioning, and product development, with a focus on building systems that protect customers and the marketplace while preserving healthy marketplace activity.

You will work on some of the most important trust and safety problems in digital logistics, including onboarding risk, behavioral risk detection, fraud and abuse detection, account integrity, network-graph risk modeling, and continuous monitoring throughout the customer lifecycle.

This is a hands-on, end-to-end science role where you will:

  • Conceptualize, propose, implement, and iterate on models and algorithms for fraud detection, risk scoring, and trust and safety decisioning.
  • Build decision engines that learn from feedback and support actions such as step-up verification, review prioritization, and automated access controls.
  • Apply machine learning, graph and network algorithms, anomaly detection, and other quantitative methods to deliver measurable improvements in fraud prevention and operational effectiveness.
  • Take ideas from research to production, ensuring the solutions you build integrate cleanly into operational and product systems.

You will be joining at a pivotal point in DAT's transformation as we automate more of the freight lifecycle and build the safest, most efficient automated marketplace in the freight industry. DAT has also accumulated a uniquely rich set of behavioral, operational, and risk data across its platforms (Convoy Platform, TruckerTools, OutGo, DAT), that enables a strong foundation for behavior-drift modeling, account and identity abuse detection, and broader threat detection systems. A key part of the opportunity is extending Convoy Platform's industry-leading CARVE product across the broader DAT ecosystem and evolving them into customer-facing risk products for a wider set of DAT customers.

This is a deeply technical role focused on building and productionizing high-recall risk models and decision systems for high-stakes compliance and trust workflows, where protecting customers, minimizing missed risk, and making decisions that are measurable, explainable, and operationally defensible all matter. Just as importantly, these systems must act like a scalpel rather than a sledgehammer: in a fair marketplace, we need to target true risk precisely, avoid unnecessary friction for legitimate participants, and make nuanced decisions that balance recall, precision, customer protection, and marketplace health.

What You'll Do

  • Build and productionize fraud, safety, and risk systems for high-recall decisioning, with controls that preserve precision, fairness, and explainability in high-stakes workflows.
  • Design graph, network-link analysis, entity-resolution, and anomaly-detection algorithms that identify hidden relationships, behavioral drift, account abuse, and emerging threat patterns across users, carriers, digital fingerprints and physical assets.
  • Develop continuous risk monitoring, alerting, and policy decisioning across onboarding, booking, and load execution, combining ML models, heuristics, feedback loops, and human-in-the-loop review where appropriate.
  • Move proactively and with urgency against evolving fraud patterns, rapidly iterating on approaches while building scalable, adaptable detection and decisioning systems rather than brittle one-off patches or manual hacks.

The Skills and Experience You'll Bring

  • PhD or MS in Computer Science, Statistics, Applied Mathematics, Operations Research, Engineering, or another quantitative field.
  • 5+ years of experience developing and deploying machine learning, statistical, or decisioning solutions in production environments, with strong proficiency in Python and modern ML tooling and hands-on experience building reliable, production-quality data and model workflows.
  • Ability to develop algorithmic solutions and decision systems while maintaining explainability, interpretability, and defensibility in high-stakes risk and compliance workflows.
  • Experience owning a model, service, API, or pipeline end-to-end, including quality, monitoring, iteration, and cross-functional coordination, with strong communication and collaboration skills to work effectively with technical and non-technical partners and bring models into production.
  • Demonstrated ability to frame ambiguous business problems as scalable automated decision systems and deliver practical solutions with measurable impact.
  • Experience in one or more of the following areas: fraud detection, trust and safety, risk modeling, anomaly detection, rare-event modeling, identity or abuse detection, graph or network analysis, or related decision systems.

Bonus Skills 

  • You have worked on systems that combine models, heuristics, human review, and operational workflows to make high-stakes decisions.
  • You have experience with two-sided marketplaces, pricing, financial markets, or economic systems.
  • You have experience in freight, logistics, transportation technology, or adjacent operational domains.

Why DAT?
DAT is an award winning employer of choice.

For starters, we have a hybrid work environment, but we also know what makes a great workplace. We have a time-tested and resolute set of operating values predicated on integrity, mutual respect, open communication, and executing with excellence. These values inform our strategic vision as much as any one of our products does. We've been an employer of choice in the Portland metropolitan area for four decades, and within one year of opening our Denver office, DAT was #26 on Built In Colorado's 100 Best Places to Work In Colorado.

  • Medical, Dental, Vision, Life, and AD&D insurance
  • Parental Leave
  • Flexible Vacation Time (FVT)
  • An additional 10 holidays of paid time off per calendar year
  • 401k matching (immediately vested)
  • Employee Stock Purchase Plan
  • Short- and Long-term disability sick leave
  • Flexible Spending Accounts
  • Health Savings Accounts
  • Employee Assistance Program
  • Additional programs - Employee Referral, Internal Recognition, and Wellness
  • Free TriMet transit pass (Beaverton Office)
  • Competitive salary and benefits package
  • Work on impactful projects in a cutting-edge environment
  • Collaborative and supportive team culture
  • Opportunity to make a real difference in the trucking industry
  • Employee Resource Groups

*This position is not eligible for visa sponsorship**

For Washington-based candidates, in compliance with the Washington State Pay Transparency Law, the salary range for this role is $183,000.00 - $226,000.00 + target bonus.  DAT considers factors such as scope and responsibilities of the position, candidate's work experience, education and training, core skills, internal equity, and market and business elements when extending an offer.

DAT embraces the value of a diverse workforce, and believes it is a core strength of our company that we encourage those values in every DAT employee, at every level of our organization, regardless of tenure or rank. We provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state, and local laws.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information. 41 CFR 60-1.35(c)

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