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Quantitative Data Engineer Jobs in Boca Raton, FL

Purposebrands

BI Analyst II

Boca Raton, FL

$90K - $115K/yr

They work with our data engineers to augment datasets to enable dashboarding, reports, and ... quantitative analysis. * 3-5 years of experience in reporting and analysis. Experience with ...

Purpose Brands LLC

BI Analyst II

Boca Raton, FL · On-site

$90K - $115K/yr

They work with our data engineers to augment datasets to enable dashboarding, reports, and ... quantitative analysis. * 3-5 years of experience in reporting and analysis. Experience with ...

DHL eCommerce

Manager Commercial Analytics

Weston, FL · On-site

... quantitative field required; master's degree in Business Analytics, * Data Science, MBA with an ... Microsoft Azure certifications (e.g., Azure Data Engineer or Azure Data Scientist) * Databricks ...

ADT

Sr. Manager, Digital Analytics

Boca Raton, FL · On-site

Collaborate with data engineering and IT partners to align on data architecture, integration, and ... quantitative field. * Strong expertise in diagnostic and causal analytics methodologies.

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All JobsQuantitative Data Engineer JobsQuantitative Data Engineer Jobs in Boca Raton, FL

Quantitative Data Engineer information

See Boca Raton, FL salary details

$10.4K

$123K

$187.9K

How much do quantitative data engineer jobs pay per year?

As of Jul 20, 2026, the average yearly pay for quantitative data engineer in Boca Raton, FL is $123,049.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,600.00 and $131,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Quantitative Data Engineer, and why are they important?

To excel as a Quantitative Data Engineer, you need strong proficiency in programming (such as Python, R, or C++), advanced mathematical and statistical knowledge, and a relevant degree in computer science, mathematics, or a related field. Experience with big data tools (like Spark, Hadoop), cloud platforms, and data pipeline systems, as well as familiarity with financial data sets, is typically required. Analytical thinking, detail orientation, and effective problem-solving skills distinguish top performers in this role. These competencies are critical for efficiently transforming complex data into actionable insights and supporting robust quantitative models in data-driven environments.

What is a Quantitative Data Engineer?

A Quantitative Data Engineer is a professional who designs, builds, and maintains data infrastructure that supports quantitative analysis, typically in finance or technology sectors. They work closely with quantitative analysts and data scientists to ensure efficient data pipelines, data quality, and high-performance systems for processing large datasets. Their responsibilities include developing ETL processes, optimizing databases, and implementing data models to support research and trading strategies. Strong programming skills, expertise in big data technologies, and knowledge of quantitative methods are essential for this role.

What is the difference between Quantitative Data Engineer vs Data Scientist?

AspectQuantitative Data EngineerData Scientist
Primary FocusBuilding data pipelines, data infrastructure, and ensuring data qualityAnalyzing data, creating models, and deriving insights
Skills & ToolsSQL, Python, Spark, ETL processes, data architectureStatistics, machine learning, Python/R, data visualization
CredentialsComputer science, engineering, or related degrees; certifications in data engineeringStatistics, data science, or related degrees; certifications in data analysis or machine learning
Work EnvironmentData engineering teams, data infrastructure projectsData analysis teams, research, and modeling projects

While both roles work closely with data, Quantitative Data Engineers focus on building and maintaining data systems, whereas Data Scientists analyze data to generate insights and models. They often collaborate but have distinct skill sets and responsibilities within data-driven organizations.

How does a Quantitative Data Engineer typically collaborate with data scientists and quantitative analysts on projects?

Quantitative Data Engineers work closely with data scientists and quantitative analysts to design, build, and optimize data pipelines that support complex modeling and analytics. They are often responsible for ensuring data quality, scalability, and efficient data processing, enabling analysts to focus on developing models and extracting insights. Regular collaboration includes translating analytical requirements into technical solutions, troubleshooting data issues, and iterating on data infrastructure to support evolving project needs. This teamwork fosters an environment where technical and analytical expertise complement each other, leading to more robust and actionable results.
What are popular job titles related to Quantitative Data Engineer jobs in Boca Raton, FL? For Quantitative Data Engineer jobs in Boca Raton, FL, the most frequently searched job titles are:
What job categories do people searching Quantitative Data Engineer jobs in Boca Raton, FL look for? The top searched job categories for Quantitative Data Engineer jobs in Boca Raton, FL are:
What cities near Boca Raton, FL are hiring for Quantitative Data Engineer jobs? Cities near Boca Raton, FL with the most Quantitative Data Engineer job openings:
Quantitative Data Engineer jobs near you
Senior Data Scientist

Senior Data Scientist

Haystack News

Fort Lauderdale, FL • On-site

Full-time

Posted 3 days ago

Job description

Haystack News, the number one destination for news on streaming platforms, is looking for a Sr Data Scientist to join our team. Haystack is trusted by over 30 million viewers and is among the fastest-growing TV news companies in the world.
Join our team at Haystack News as a Senior Data Scientist and become a pivotal force in redefining user experiences through cutting-edge algorithm enhancements. In this role, you'll leverage your advanced statistical analysis, modeling, causal inference, experimental design (A/B testing) and data analytics expertise to drive substantial improvements in user engagement and retention, directly impacting our product's success. This is an exceptional opportunity to showcase your robust problem-solving capabilities and to thrive in a collaborative environment, working alongside a team of passionate professionals dedicated to innovation and excellence. Be part of a dynamic workplace where your contributions make a meaningful difference and help shape the future of news consumption.
MINIMUM QUALIFICATIONS
  • PhD or M.S. in Computer Science, Mathematics, Electrical Engineering, Statistics, Economics or Operations Research with 5+ years of professional experience in data science, machine learning or related quantitative field
  • 3+ years of professional experience with large-scale online ranking/recommender systems (for news feeds, shopping, ads, music, etc).
  • Deep expertise in statistical inference and experimental design: hypothesis testing, power/sample size calculations, variance reduction, etc.
  • Proficiency in causal inference methods to measure product impact.
  • Proven ability to translate offline analysis into product decisions and measurable improvements in online metrics.
  • Fluency in the Python analytics stack (pandas, NumPy), statistical modeling (statsmodels or scikit-learn) and machine learning packages such as LightGBM and XGBoost.
  • Strong experience with SQL (e.g. postgres, snowflake, etc).

PREFERRED QUALIFICATIONS:
  • Experience working on consumer-facing products with millions of users.
  • Hands-on experience with orchestration/transformation tools (e.g. dbt and Airflow).
  • Experience with deep learning and being familiar with tools such as PyTorch or TensorFlow.
  • Hands-on development of products/tools incorporating GenAI, LLMs, RAG, and/or Agents.

RESPONSIBILITIES
  • Build statistical and machine learning models to improve content discovery and user engagement.
  • Work closely with ML engineers to translate models and insights into production systems.
  • Have curiosity and apply analytical skills to dive deep into data to find key insights that would impact the business.
  • Apply causal inference methods to understand the impact of potential product changes.
  • Define and build new ML features using text and multimodal embeddings and GenAI.
  • Validate offline learnings with online outcomes through AB testing. Design, execute, and analyze experiments to prove product change attribution.

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