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Manager Algorithmic Trading Quant Jobs in Miami, FL

Machine Learning Engineer

Miami, FL · On-site

$80 - $120/hr

They'll be working on cutting edge Quantitative Data Analysis and Machine Learning challenges. Our ... Utilize knowledge of classical machine learning and deep learning algorithms to address specific ...

... trading services to active customers, security structure and market analysis, and provision of ... Exempt: Nonexempt: Sales Budget (If Applicable) $ Other Relevant quantitative data: Problem Solving ...

... management problems in aviation involving complex trade-offs under uncertainty. You will ... Strong understanding of statistical modeling, machine learning algorithms, hypothesis testing, and ...

... Quantitative Trading. We are seeking a highly motivated PM Engagement Analyst to support the senior PM Engagement team in their work with Portfolio Managers and analysts within our Long/Short Equity ...

Showing results 41-60

Manager Algorithmic Trading Quant information

See Miami, FL salary details

$23.4K

$56.9K

$110.9K

How much do manager algorithmic trading quant jobs pay per year?

As of Aug 10, 2026, the average yearly pay for manager algorithmic trading quant in Miami, FL is $56,932.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,200.00 and $65,500.00 per year, depending on experience, location, and employer.

What is the difference between Manager Algorithmic Trading Quant vs Quantitative Trader?

AspectManager Algorithmic Trading QuantQuantitative Trader
Primary RoleOversees trading strategies, manages teams, and develops high-level algorithmsExecutes trading strategies, analyzes markets, and implements models
ResponsibilitiesStrategy development, team leadership, risk managementMarket analysis, trade execution, model testing
CredentialsAdvanced degrees in finance, math, or computer science; experience in tradingDegree in finance, math, or related fields; strong quantitative skills
Work EnvironmentFinancial firms, hedge funds, trading desksTrading floors, financial institutions, hedge funds

The Manager Algorithmic Trading Quant focuses on leading teams and developing high-level trading algorithms, while the Quantitative Trader primarily executes trades and analyzes markets. Both roles require strong quantitative skills and relevant credentials, but differ in responsibilities and leadership scope.

What are the most commonly searched types of Algorithmic Trading Quant jobs in Miami, FL? The most popular types of Algorithmic Trading Quant jobs in Miami, FL are:
What are popular job titles related to Manager Algorithmic Trading Quant jobs in Miami, FL? For Manager Algorithmic Trading Quant jobs in Miami, FL, the most frequently searched job titles are:
What job categories do people searching Manager Algorithmic Trading Quant jobs in Miami, FL look for? The top searched job categories for Manager Algorithmic Trading Quant jobs in Miami, FL are:
What cities near Miami, FL are hiring for Manager Algorithmic Trading Quant jobs? Cities near Miami, FL with the most Manager Algorithmic Trading Quant job openings:
Infographic showing various Manager Algorithmic Trading Quant job openings in Miami, FL as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 14% Part Time, and 1% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $56,932 per year, or $27.4 per hour.

Data Scientist, Revenue Management Systems

Norwegian Cruise Line Holdings Ltd

Miami, FL • On-site

Full-time

Re-posted 2 days ago


Job description

GROW YOUR CAREER WITH US
At Norwegian Cruise Line Holdings (NCLH), we know our future success depends on our ability to attract and retain the very best talent. Our brands deliver vacations of a lifetime with innovative product offerings, a high level of service and unique guest experiences aboard each vessel and we're continually seeking applicants who are passionate about hospitality and committed to being their personal best. As you learn more about our company, we think you will agree that there is no better time than now to become a member of the NCLH family!
APPLY ONLINE
If you're interested to be considered for this position, please click the blue APPLY button at the top of the page to get started. All candidates must complete an on-line application to be considered.
JOB SUMMARY
The Data Scientist within Revenue Management Systems will be responsible for building, scaling, and validating the predictive models, forecasting logic, and advanced analytics frameworks that power Norwegian Cruise Line's dynamic pricing and inventory management decisions. This individual contributor role bridges statistical engineering with commercial operations-translating massive datasets, historical transaction curves, and high-intent guest behavioral data into clear, high-yield revenue recommendations.
Working closely with senior leadership, data engineers, and revenue managers, the Data Scientist will write production-grade SQL and Python code to design scalable forecasting algorithms and price elasticity frameworks. The ideal candidate thrives on extracting value from complex database environments (e.g., Snowflake) and converting technical model performance into clear business insights.
POSITION RESPONSIBILITIES
  • Predictive Model Construction: Design, write, and maintain scalable algorithms and machine learning models for booking curves, price elasticity, cancellation rates, and passenger cabin upgrades (e.g., Plusgrade).
  • Data Pipeline & ETL Engineering: Query, clean, aggregate, and manipulate large-scale datasets from disparate corporate ecosystems using Snowflake, SQL, and Python to ensure reliable inputs for quantitative modeling.
  • RMS Calibration & Evaluation: Monitor, fine-tune, and analyze baseline calibration thresholds within enterprise Revenue Management Systems (RMS) to reduce forecast variances and automate routine algorithmic workflows.
  • A/B Testing & Attribution: Formulate rigorous tracking and measurement frameworks, using statistical methodologies and panel data techniques to validate the exact revenue impacts of tactical promotions and digital pricing optimizations.
  • Business Intelligence Support: Architect, deploy, and maintain insightful data visualization dashboards in Power BI or Tableau to translate modeling results and performance metrics into clear stories for commercial stakeholders.
  • Cross-Functional Collaboration: Partner closely with IT and data engineering teams to operationalize prototypes into robust production systems, while communicating quantitative logic clearly to non-technical business partners.

QUALIFICATIONS
DEGREE TYPE:
Bachelor's Degree
FIELD(S) OF STUDY:
Business Administration, Hospitality Management, Finance, Marketing, or a related field
EXPERIENCE
  • Bachelor's degree in Data Science, Statistics, Mathematics, Operations Research, Economics, Computer Science, or a heavily quantitative discipline is required.
  • Master's degree (MS) in a quantitative field is a plus but not required with equivalent professional experience.
  • 3-5 years of progressive professional experience working as a data scientist, quantitative analyst, or modeler-ideally building systems that influence business pricing, sales, or financial forecasting.
  • Hands-on experience manipulating, structuring, and scrubbing large, raw datasets within enterprise cloud-based or local architectures.
  • Prior experience working in dynamic commercial fields with highly perishable inventory (e.g., cruise lines, aviation, hospitality, logistics, or consumer tech) is highly preferred.
  • Experience in a role that required presenting complex outputs in clear and concise way that influenced leadership.

COMPETENCIES & SKILLS
  • Advanced Querying & Coding: Strong mastery of programming languages required for statistical computing, data architecture, and ETL execution, specifically Python and advanced SQL.
  • Cloud Environments: Hands-on familiarity extracting and joining complex relational data within cloud data platforms like Snowflake, Databricks, or cloud equivalents.
  • Data Visualization: Demonstrated capability building, hosting, and automating reports or data visualization dashboards in Power BI or Tableau.
  • Statistical & ML Frameworks: Knowledge of regression analysis, time-series forecasting ARIMA/Prophet, optimization algorithms, and common machine learning packages (scikit-learn, XGBoost, etc.).
  • Analytical Curiosity: A natural drive to unearth trends in chaotic, complex transaction data and translate those findings into logical business mechanics.
  • Execution & Delivery: Strong time management skills with a proven capacity to take an abstract business request and run with it from exploratory data analysis to model testing and dashboard delivery.
  • Collaborative Communicator: Ability to speak comfortably with both database administrators and non-technical business leaders, ensuring complex modeling results are easily understood.

ABOUT NCLH
Norwegian Cruise Line Holdings Ltd. (NYSE: NCLH) is a leading global cruise company which operates the Norwegian Cruise Line®, Oceania Cruises® and Regent Seven Seas Cruises® brands. The combined brands currently operate 32 ships, employ over 35,000 shipboard crew from more than 110 different countries and visit approximately 700 different port destination each year.
LEARN MORE ABOUT OUR COMPANY:
At a Glance
Brand Overview
Norwegian Cruise Line
Oceania Cruises
Regent Seven Seas Cruises
New Releases
EQUAL OPPORTUNITY EMPLOYER
It is Norwegian Cruise Line Holding's policy not to discriminate against any employee or applicant for employment because of race, color, religion, sex, national origin, age, disability, and marital or veteran status.
The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not to be construed as an exhaustive list of all responsibilities, duties, and skills required of personnel so classified. All personnel may be required to perform duties outside of their normal responsibilities from time to time, as needed.