In this role, you will bridge strategy and execution-translating complex business problems into ... Lead the design, development, and deployment of statistical models, machine learning algorithms ...
In this role, you will bridge strategy and execution-translating complex business problems into ... Lead the design, development, and deployment of statistical models, machine learning algorithms ...
Forward Deployed Engineer
Southfield, MI · On-site
Proven track record of deploying predictive AI models and optimization algorithms to solve business ... quantitative field * Experience in supply chain, logistics, or transportation operations
Forward Deployed Engineer
Southfield, MI · On-site
Proven track record of deploying predictive AI models and optimization algorithms to solve business ... quantitative field * Experience in supply chain, logistics, or transportation operations
Algorithmic Execution Quant information
See Ann Arbor, MI salary details
$51.4K - $64.2K
4% of jobs
$64.2K - $77K
17% of jobs
$78.8K is the 25th percentile. Wages below this are outliers.
$77K - $89.8K
29% of jobs
$89.8K - $102.6K
0% of jobs
$102.6K - $115.4K
2% of jobs
$115.4K - $128.2K
7% of jobs
$128.2K - $141K
7% of jobs
$147.8K is the 75th percentile. Wages above this are outliers.
$141K - $153.8K
16% of jobs
$153.8K - $166.6K
7% of jobs
$166.6K - $179.4K
5% of jobs
$179.4K - $192.2K
5% of jobs
$51.4K
$116.6K
$192.2K
How much do algorithmic execution quant jobs pay per year?
As of Aug 29, 2026, the average yearly pay for algorithmic execution quant in Ann Arbor, MI is $116,583.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,800.00 and $149,200.00 per year, depending on experience, location, and employer.
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 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.
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.
What is the difference between Algorithmic Execution Quant vs Quantitative Trader?
| Aspect | Algorithmic Execution Quant | Quantitative Trader |
|---|---|---|
| Primary Focus | Developing and implementing algorithms for trade execution to minimize market impact | Creating trading strategies to generate alpha and profit from market movements |
| Work Environment | Quantitative research teams, trading desks, technology-driven | Trading floors, portfolio management teams, research departments |
| Required Skills | Programming, market microstructure, execution algorithms | Quantitative 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 are popular job titles related to Algorithmic Execution Quant jobs in Ann Arbor, MI?
For Algorithmic Execution Quant jobs in Ann Arbor, MI, the most frequently searched job titles are:
What job categories do people searching Algorithmic Execution Quant jobs in Ann Arbor, MI look for?
The top searched job categories for Algorithmic Execution Quant jobs in Ann Arbor, MI are:
What cities near Ann Arbor, MI are hiring for Algorithmic Execution Quant jobs?
Cities near Ann Arbor, MI with the most Algorithmic Execution Quant job openings:
Full-time
Medical, Dental, Vision, Retirement
Re-posted 7 days ago
Job description
OneMagnify is an AI native, platform-enabled B2B digital agency operating at the intersection of data, technology, and creativity. We help complex organizations drive measurable business outcomes by building smarter customer experiences and delivering highly integrated solutions across digital, media, and technology. By combining deep industry expertise with advanced analytics and artificial intelligence, we enable our clients to make better decisions, move faster, and compete more effectively in dynamic markets.
You'll be joining our RXA Data Science team, a group dedicated to leveraging advanced analytics, predictive modeling, and machine learning to drive smarter marketing and business decisions. As Lead Data Scientist, you will play a critical role in delivering impactful, data-driven solutions. In this role, you will bridge strategy and execution-translating complex business problems into analytically sound solutions while ensuring technical excellence, timely delivery, and cross-functional collaboration.
The Lead Data Scientist is responsible for leading the execution of end-to-end data science projects, from scoping and modeling to operationalization and insight delivery. You will partner with clients, internal teams, and technical stakeholders to develop and deploy scalable solutions that drive measurable business value.
What you'll do:
Lead the design, development, and deployment of statistical models, machine learning algorithms, and custom analytics solutions
Collaborate consistently with team members to understand the purpose, focus, and objectives of each data analysis project, ensuring alignment and meaningful support
Translate client goals into clear modeling strategies, project plans, and deliverables
Guide the development of production-level model pipelines using tools such as Databricks and Azure ML
Collaborate with engineering, marketing, and strategic partners to integrate models into real-world applications
Monitor and improve model performance, ensuring high standards for reliability and business relevance
Present complex analytical results to technical and non-technical audiences in a clear, actionable format
Support innovation by identifying new tools, methods, and data sources-including the use of Snowflake for modern data architecture
Promote best practices in model governance, data ethics, and responsible AI
What you need:
Minimum 5-7 years of experience in data science, analytics, or predictive modeling
Experience leading all aspects of sophisticated data science initiatives with a solid foundation in technical strategy and execution
Strong programming skills in Python, R, or SAS for modeling and data analysis
Advanced SQL capabilities and experience working in cloud-based environments (e.g., Azure, AWS)
Hands-on experience with Databricks, Azure Machine Learning, and Snowflake strongly preferred
Experience applying the modeling rigor and documentation standards required in regulated industries such as financial services is a strong plus
Expertise in regression, classification, clustering, A/B testing, and audience segmentation
Proficiency with Tableau, Power BI, and Excel for data visualization and communication
Strong communication skills and the ability to translate complex technical findings into business insight
Bachelor's degree in Data Science, Statistics, Computer Science, or a related quantitative field (Master's preferred)
Experience in integrated marketing, digital agency, marketing services, or consulting environments preferred.
Benefits
We believe great work happens when people have the support and flexibility they need to thrive. Our benefits include medical, dental, and vision coverage, a 401(k) retirement plan, paid holidays, and Flexible Time Off (FTO) so you can take time away to recharge when you need it. We also offer additional programs focused on wellness, financial security, and professional growth.
We are an equal opportunity employer
We believe that Innovative ideas and solutions start with unique perspectives. That's why we're committed to providing every employee a workplace that's free of discrimination and intolerance. We're proud to be an equal opportunity employer and actively search for like-minded people to join our team.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform job functions, and to receive benefits and privileges of employment. Please contact us to request accommodation.