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Algorithmic Execution Quant Jobs in Utah (NOW HIRING)

You are a deeply data-driven "quant marketer" who is just as comfortable debating incrementality ... You know the inner workings of the ad algorithms, not just the front-end dashboards. * Elite Ad ...

You are a deeply data-driven "quant marketer" who is just as comfortable debating incrementality ... You know the inner workings of the ad algorithms, not just the front-end dashboards. * Elite Ad ...

You are a deeply data-driven "quant marketer" who is just as comfortable debating incrementality ... You know the inner workings of the ad algorithms, not just the front-end dashboards. * Elite Ad ...

Algorithmic Execution Quant information

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 are popular job titles related to Algorithmic Execution Quant jobs in Utah? For Algorithmic Execution Quant jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Algorithmic Execution Quant jobs in Utah look for? The top searched job categories for Algorithmic Execution Quant jobs in Utah are:
What cities in Utah are hiring for Algorithmic Execution Quant jobs? Cities in Utah with the most Algorithmic Execution Quant job openings:
Data Scientist - Applied AI Scientist

Data Scientist - Applied AI Scientist

Zions Bank

Midvale, UT • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago


Job description

Zions Bancorporation's Enterprise Technology and Operations (ETO) team is transforming what it means to work for a financial institution. With a commitment to technology and innovation, we have been providing our community, clients and colleagues the best experience possible for over 150 years. Help us transform our workforce of the future, today.
Zions Bancorporation's Innovation Lab is seeking a creative and driven Data Scientist (Applied AI Scientist) who bridges the gap between rigorous statistical research and production-grade software engineering. This role is at the heart of our innovation engine. You will not only uncover deep data insights and design advanced AI algorithms, but you will also architect the robust, scalable code required to bring those concepts to life.
As a key member of the Innovation Lab, you will work in a fast-paced, experimental environment, turning ambiguous business challenges into tangible, data-driven prototypes. We need a scientist who treats machine learning as an engineering discipline, someone who understands the "why" behind the math, and the "how" of robust software implementation.
Visa Sponsorship:
This Data Scientist position is currently NOT eligible for employment visa sponsorship (e.g., H-1B visa). This includes, for example, situations where a candidate may have temporary work authorization while enrolled in school or upon graduation (e.g., CPT, OPT) but would need H-1B visa sponsorship within a few years of employment in order to maintain employment eligibility.
Responsibilities:
  • End-to-End AI Design: Design, prototype, and validate ML/AI solutions, translating complex business challenges into mathematical formulations and scalable, production-ready code.
  • Advanced Analytics & EDA: Perform deep exploratory data analysis, statistical testing, and data transformations on diverse datasets (structured and unstructured) to uncover predictive signals and validate hypotheses.
  • Production-Grade Science: Architect and implement modular, extensible, and testable Python codebases for AI experiments. Move beyond Jupyter notebooks by applying clean-code principles (SOLID, DRY) for seamless hand-off to ETO Engineering teams.
  • Agentic & Generative AI: Develop and experiment with applied generative AI and multi-agent architectures using orchestration frameworks (e.g., LangChain, LangGraph), focusing on optimal state management, robust RAG pipelines, and efficient system design.
  • Algorithmic Optimization: Optimize model inference, data processing pipelines, and memory footprints for latency and scalability, applying a strong understanding of data structures and algorithmic complexity.
  • Rigorous Evaluation: Build automated evaluation frameworks to benchmark model performance, mitigate hallucinations, track drift, and ensure algorithmic fairness via A/B testing and statistical rigor.
  • Collaboration & Communication: Act as the technical translator between research-focused ideation and engineering execution. Communicate complex statistical findings and system architectures to both technical and non-technical stakeholders.

Qualifications:
  • The Scientist's Mind: Solid foundation in statistics (Bayesian/Frequentist), linear algebra, hypothesis testing, and the internal mechanics of ML algorithms (e.g., how optimizers work, loss functions, attention mechanisms).
  • The Engineer's Toolbelt: Advanced Python proficiency with a strong focus on Object-Oriented Programming (OOP) and modular design. You must be comfortable writing unit tests (e.g., Pytest) for your data pipelines and models.
  • Framework Depth: Deep expertise with ML libraries (PyTorch, TensorFlow, Scikit-learn, Pandas) and experience implementing custom logic, rather than just calling out-of-the-box models.
  • Generative AI Systems: Hands-on experience with NLP, Large Language Models (LLMs), and Vector Databases, with an understanding of how to evaluate and optimize these systems at scale.
  • Software Maturity: Proficiency with Git/version control, containerization (Docker), API development (FastAPI/Flask), and a working knowledge of how models fit into a CI/CD lifecycle (MLOps).
  • Problem Solving: Exceptional problem-solving skills, comfort with ambiguity, and the ability to own the data science lifecycle from abstract ideation to engineered prototype.
  • Education & Experience: Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field plus 4+ years of hands-on experience in applied machine learning or data science. A Master's degree or PhD is a plus. A combination of education and experience may meet qualifications.

Location:
This position has a hybrid work from home schedule with a minimum of three days per week in the office at the new Zions Technology Center in Midvale, UT.
The Zions Technology Center is a 400,000-square-foot technology campus in Midvale, Utah. Located on the former Sharon Steel Mill superfund site, the sustainably built campus is the company's primary technology and operations center. This modern and environmentally friendly technology center enables Zions to compete for the best technology talent in the state while providing team members with an exceptional work environment with features such as:
  • Electric vehicle charging stations and close proximity to Historic Gardner Village UTA TRAX station.
  • At least 75% of the building is powered by on-site renewable solar energy.
  • Access to outdoor recreation, parks, trails, shareable bikes and locker rooms.
  • Large modern cafe with a healthy and diverse menu.
  • Healthy indoor environment with ample natural light and fresh air.
  • LEED-certified sustainable building that features include the use of low VOC-emitting construction materials.

Benefits:
  • Medical, Dental and Vision Insurance - START DAY ONE!
  • Life and Disability Insurance, Paid Parental Leave and Adoption Assistance
  • Health Savings (HSA), Flexible Spending (FSA) and dependent care accounts
  • Paid Training, Paid Time Off (PTO) and 11 Paid Federal Holidays
  • 401(k) plan with company match, Profit Sharing, competitive compensation in line with work experience
  • Mental health benefits including coaching and therapy sessions
  • Tuition Reimbursement for qualifying employees
  • Employee Ambassador preferred banking products

#dice

Zions Bank logo

About Zions Bank

Sourced by ZipRecruiter

Zions Bank recognizes that its success comes from the dedication, experience and talents of its diverse employee base. As we usher in the next generation of banking, we're committed to being the premier employer of choice. We're proud to have ranked among American Banker magazine's "Best Banks to Work For" almost every year since 2013, as Best Employer from Utah's Best of State, among the Best Places to Work in Idaho, and "among the Salt Lake Tribune's Top Workplaces. Make the leap into a new era of banking. Let us transform your career.

Industry

Commercial banking

Company size

1,001 - 5,000 Employees

Headquarters location

Salt Lake City, UT, US

Year founded

1873

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