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Quant Python Remote Jobs in Hyattsville, MD (NOW HIRING)

TS/SCI with Poly Potential for Remote Work: ORA_ON_SITE Description The Data Scientist will apply ... Create and edit visual content, including charts, graphs, and dashboards, to transform quantitative ...

IoT / Edge Software Engineer

Bethesda, MD ยท Remote

$68K - $141K/yr

We are currently seeking a IoT / Edge Software Engineer to join our team in Bethesda (REMOTE ... Proficiency in Python, Java, or similar languages used for backend and API development

Senior Generative AI Engineer

Potomac, MD ยท Remote

$56.50 - $73/hr

Python fluency including LangChain and AWS Strands; experience with vector databases and embedding ... Remote location but greater Washington, DC area preferred for hybrid engagement * Sponsored AWS ...

Data Scientist

Reston, VA ยท On-site +1

Quantitative Finance * Statistics * Experience analyzing real world data through coursework, thesis ... Ability to analyze data in Python or another Object-Oriented Programming Language * Ability to ...

Data Scientist

Reston, VA ยท On-site +1

Quantitative Finance * Statistics * Experience analyzing real world data through coursework, thesis ... Ability to analyze data in Python or another Object-Oriented Programming Language * Ability to ...

Senior Generative AI Engineer

Washington, DC ยท On-site +1

$62.50 - $80.75/hr

Python fluency including LangChain and AWS Strands; experience with vector databases and embedding ... Remote location but greater Washington, DC area preferred for hybrid engagement * Sponsored AWS ...

Senior Generative AI Engineer

Potomac, MD ยท On-site +1

$57.25 - $73.75/hr

Python fluency including LangChain and AWS Strands; experience with vector databases and embedding ... Remote location but greater Washington, DC area preferred for hybrid engagement * Sponsored AWS ...

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Quant Python Remote information

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How much do quant python remote jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for quant python remote in Hyattsville, MD is $58.76, according to ZipRecruiter salary data. Most workers in this role earn between $48.41 and $66.73 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Quant Python Remote professional, and why are they important?

To thrive as a Quant Python Remote professional, you need a strong background in quantitative analysis, mathematics, and expertise in Python programming, often supported by a degree in a quantitative field. Familiarity with libraries like NumPy, pandas, and scikit-learn, as well as experience with version control systems and cloud-based collaboration tools, is typically required. Strong problem-solving abilities, attention to detail, and effective remote communication skills help distinguish top performers in this role. These competencies are crucial for developing robust quantitative models, collaborating efficiently across distributed teams, and driving data-driven decision-making in finance or related sectors.

What is a Quant Python Remote job?

A Quant Python Remote job involves working as a quantitative analyst or developer, focusing on financial modeling, data analysis, and algorithmic trading using Python, all while working remotely. Professionals in this role use Python to develop quantitative strategies, analyze financial data, and create tools for risk management or trading. These jobs are popular in hedge funds, investment banks, and fintech companies seeking experts who can work from anywhere. Strong programming skills, knowledge of statistics, and experience in finance are typically required.

What is the difference between Quant Python Remote vs Quantitative Analyst?

AspectQuant Python RemoteQuantitative Analyst
Required CredentialsDegree in Math, Stats, or CS; Python proficiency; sometimes certificationsDegree in Finance, Math, or Economics; strong programming skills; certifications like CFA are common
Work EnvironmentRemote, flexible hours, often self-directedTypically office-based, but increasingly remote; collaborative teams
Employer & IndustryFinancial firms, hedge funds, fintech companiesInvestment banks, asset management firms, hedge funds
Search & Comparison IntentLooking for remote Python-based quant rolesSeeking quantitative analysis roles in finance

While both roles involve quantitative skills and finance knowledge, Quant Python Remote emphasizes remote work and Python programming, whereas Quantitative Analyst roles may be more traditional and office-based, often requiring finance-specific certifications. Candidates should consider their preferred work environment and skill set when choosing between these roles.

What are some typical challenges faced by Quant Python professionals working remotely, and how can they be addressed?

Quant Python professionals working remotely often encounter challenges such as collaborating effectively with team members across different time zones, maintaining clear communication on complex quantitative models, and ensuring secure access to sensitive financial data. To address these issues, it's important to utilize robust collaboration tools (like Slack or Zoom), establish regular check-ins with teammates, and follow best practices for code documentation and version control. Additionally, many employers provide secure VPNs and cloud-based platforms to facilitate safe data access, helping remote quants stay productive and connected.
What are popular job titles related to Quant Python Remote jobs in Hyattsville, MD? For Quant Python Remote jobs in Hyattsville, MD, the most frequently searched job titles are:
What job categories do people searching Quant Python Remote jobs in Hyattsville, MD look for? The top searched job categories for Quant Python Remote jobs in Hyattsville, MD are:
What cities near Hyattsville, MD are hiring for Quant Python Remote jobs? Cities near Hyattsville, MD with the most Quant Python Remote job openings:
AI/ML Engineer, Senior - WFH1650

AI/ML Engineer, Senior - WFH1650

Global InfoTek, Inc.

Reston, VA โ€ข On-site, Remote

$108K - $149K/yr

Full-time

Posted 27 days ago


Job description

Clearance Level: Public Trust
US Citizenship: Required
Job Classification: Full Time
Location: Remote
Years of Experience: 5-7 years of relevant experience
Education Level: BS or MS in Electrical Engineering, Computer Science, Applied Mathematics, or a closely related quantitative field. Experience may be considered in place of education requirement.
Briefly Describe the Work:
GITI is seeking a Senior AI/ML Engineer to support an R&D program focused on passive RF emitter identification and network analysis from real-time sensor data streams. The Senior AI/ML Engineer designs, builds, and validates machine learning models for RF emitter identification, conducts hands-on exploratory data analysis on NDF (Network Description File) sensor datasets, and implements ML data pipelines that operate on constrained tactical edge hardware. Working under the direction of the Principal AI/ML Engineer and program technical lead, the candidate collaborates closely with research scientists and software engineers to translate analytical findings into reproducible, well-documented ML experiments and pipeline components. The role requires strong Python and deep learning skills, comfort with real-world noisy sensor data, and the ability to work in air-gapped Linux environments without cloud infrastructure or GPU acceleration.
Responsibilities:
  • Design, build, and validate machine learning models for RF emitter identification - including feature engineering from sensor data, training pipeline development, model evaluation, and iterative refinement based on results
  • Conduct hands-on exploratory data analysis on RF sensor datasets using Python and Jupyter notebooks - writing and running analytical code, characterizing feature distributions, identifying data quality issues, and producing documented findings
  • Implement and maintain ML data pipelines - ingesting NDF sensor streams, applying rollup and preprocessing logic, constructing training datasets, and ensuring pipeline correctness on constrained edge hardware with no cloud dependency
  • Collaborate with the technical lead and Principal AI/ML Engineer to investigate RF sensor data quality, attribution reliability, and feature behavior under contention - writing code to characterize error sources, validate assumptions, and reproduce findings
  • Produce clear technical documentation of experiments, model configurations, and results - maintaining reproducibility through disciplined versioning, and contributing to monthly status reports and team knowledge sharing

Career level with a complete understanding and wide application of machine learning principles and data science techniques. Working under general direction from the Principal AI/ML Engineer, executes independently on assigned modeling and analysis tasks, contributes to pipeline development, and produces reproducible, well-documented results. Bachelor's or Master's (or equivalent) with 5-7 years of hands-on applied experience.
Required Skills:
  • 5+ years of hands-on applied experience in machine learning, data science, or RF signal processing
  • Demonstrated proficiency in Python for ML and data science work - PyTorch or TensorFlow for model development, Pandas/NumPy for data manipulation, and scikit-learn or similar for evaluation and baseline modeling
  • Hands-on experience designing, training, and evaluating deep learning models - particularly metric learning, Siamese networks, or other similarity-learning architectures - on real-world, noisy, imbalanced datasets
  • Practical experience handling real-world data quality problems - missing values, label noise, class imbalance, systematic bias, and sensor artifacts - and the ability to diagnose and address them without discarding valid data
  • Ability to develop and run ML pipelines on Linux-based systems without cloud infrastructure or GPU acceleration - optimizing for CPU-only inference and multi-threaded data processing on resource-constrained x86 hardware

Desired Skills:
  • Familiarity with RF signal characteristics, passive receiver phenomenology, and sensor data interpretation - including awareness of processing artifacts, attribution ambiguities, and measurement limits common in signals intelligence datasets
  • Hands-on experience applying machine learning - particularly metric learning, deep learning networks, or similarity-learning architectures - to RF or time-series signal data, including feature engineering, training pipeline development, and model validation
  • Exposure to TDMA network protocols or military datalink systems, and interest in learning the signal processing challenges of dense, contested electromagnetic environments
  • Familiarity with direction-finding, time-difference-of-arrival (TDOA), or related passive geolocation concepts - understanding of their mathematical foundations and common failure modes is more important than operational experience
  • Experience with binary serialization formats (FlatBuffers, Protocol Buffers) and high-throughput sensor data pipelines operating in near-real-time on resource-constrained hardware
  • Background in statistical signal processing - error ellipses, bearing estimation uncertainty, feature reliability under noise - with the ability to distinguish statistically significant findings from artifacts of small sample size or improper normalization

Relevant Certifications:
  • Certifications in machine learning, data science, or related technical fields (e.g., TensorFlow Developer Certificate; PyTorch Certified Associate; AWS Certified Machine Learning - Specialty; Microsoft Certified: Azure AI Engineer Associate; Certified Analytics Professional (CAP); etc.)

Global InfoTek, Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability.
About Global InfoTek, Inc. Global InfoTek Inc. has an award-winning track record of designing, developing, and deploying best-of-breed technologies that address the nation's pressing cyber and advanced technology needs. GITI has rapidly merged pioneering technologies, operational effectiveness, and best business practices for over two decades.