2

Quant Python Remote Jobs in Washington (NOW HIRING)

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

Strong Python skills and experience with ML frameworks such as PyTorch or JAX. * Hands-on ... Strong understanding of experimental design, model evaluation, and quantitative analysis.

You have strong math/quantitative skills and excellent attention to detail. * You are curious about ... SQL, Python data tools (Pandas, NumPy, or similar) * Building simple data pipelines or analysis ...

You have strong math/quantitative skills and excellent attention to detail. * You are curious about ... SQL, Python data tools (Pandas, NumPy, or similar) * Building simple data pipelines or analysis ...

You have strong math/quantitative skills and excellent attention to detail. * You are curious about ... SQL, Python data tools (Pandas, NumPy, or similar) * Building simple data pipelines or analysis ...

You have strong math/quantitative skills and excellent attention to detail. * You are curious about ... SQL, Python data tools (Pandas, NumPy, or similar) * Building simple data pipelines or analysis ...

Leverage Python and SQL to fuse NEI-derived insights with other information sources to develop ... remote sensing, defense, or intelligence applications. * Data & Tooling Proficiency: High ...

Public Health Analyst

Vienna, VA · On-site +1

$57K - $60K/yr

This is a remote role but proximity to the Atlanta area is desired. Some Key Responsibilities ... R and Python skills are preferred for data management and basic statistical analysis. * Knowledge ...

Education: Bachelor's degree in a quantitative field (data science, statistics, mathematics ... Strong Python (pandas, NumPy, scikit-learn) and advanced SQL on large, complex datasets. Prefer ...

Showing results 41-60

Quant Python Remote information

What is a Quant Python Remote?

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 are the key skills and qualifications needed to thrive as a Quant Python Remote professional?

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 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 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 job categories do people searching Quant Python Remote jobs in Washington look for?

The top searched job categories for Quant Python Remote jobs in Washington are:

What cities in Washington are hiring for Quant Python Remote jobs?

Cities in Washington with the most Quant Python Remote job openings:

Principal Scientist - AI/ML Specialization - WFH1651

Global InfoTek, Inc.

Reston, VA • On-site, Remote

Full-time

Re-posted just now


Job description

Clearance Level:

US Citizenship: Required

Job Classification: Full Time

Location: Remote

Years of Experience: 10+ years of relevant experience

Education Level: Advanced degree (MS or PhD) 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 Principal Scientist to serve as the senior technical authority on an R&D program focused on passive RF emitter identification and network analysis from real-time sensor data streams. The Principal Scientist leads independent, hands-on analysis of NDF (Network Description File) sensor datasets, provides technical direction across parallel research threads, and serves as the primary technical advisor to the government sponsor. The role spans the full research lifecycle: formulating hypotheses, writing and executing analytical code in Python and Jupyter notebooks, interpreting and validating results, and communicating findings to both technical peers and non-specialist stakeholders. This is a deeply technical, hands-on position - the Principal Scientist conducts analysis directly and does not delegate technical work as a substitute for personal proficiency. The candidate will work within a small, distributed team operating in air-gapped Linux environments on resource-constrained tactical edge hardware, with no cloud computing.

Responsibilities:

  • Conduct independent, hands-on data analysis on RF sensor datasets using Python and Jupyter notebooks - formulating hypotheses, writing and running analytical code, interpreting results, and producing findings that directly advance program research objectives
  • Provide technical advice and research direction across a multidisciplinary team; define analytical objectives, review and validate technical outputs from AI/ML engineers and software developers, and ensure coherence across parallel research threads
  • Serve as primary technical advisor to the government sponsor: translate operational requirements into research objectives, communicate findings clearly to non-specialist stakeholders, and maintain program alignment with sponsor priorities through written reports and technical presentations
  • Design and execute analytical investigations into RF sensor data quality, emitter behavior, and attribution reliability - including characterizing error sources, identifying systematic artifacts, and developing methods to distinguish real physical signatures from sensor or processing artifacts
  • Produce technical documentation - working notes, research findings, monthly status reports, and briefing materials - that accurately represent the scope and confidence level of analytical results

Expert-level career professional recognized as a technical authority in RF systems, signals intelligence, or a closely related applied domain. Exercises broad independent judgment in defining research approach, evaluating methods, and interpreting results. Operates with minimal supervision; accountable for the scientific integrity and practical relevance of program research outputs. Advanced degree (MS or PhD) with 10+ years of hands-on applied R&D experience.

Required Skills:

  • 10+ years of hands-on applied R&D experience in RF systems, signals intelligence, electronic warfare, or related domains.
  • Proven ability to quickly acquire domain knowledge; specifically in the areas of wireless digital communications and military techniques, tactics, and procedures
  • Demonstrated ability to independently develop and execute data analyses in Python or equivalent tools on real sensor datasets; must be capable of writing production-quality analytical code, not merely directing others to do so
  • Experience addressing common problems with large quantities of real-world data, such as imputation, noise, bias, and errors
  • Track record of working effectively on constrained-hardware edge systems - no cloud, no discrete GPU - with attention to computational efficiency and multi-core, multi-thread performance on x86 platforms

Desired Skills:

  • Deep familiarity with RF signal characteristics, sensor phenomenology, and the interpretation of passive receiver data - including recognition of processing artifacts, attribution ambiguities, and the limits of sensor-derived measurements
  • 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
  • Familiarity with TDMA network protocols, emitter identification techniques (CID/PID), and the signal processing challenges of dense, contested electromagnetic environments
  • Experience with interferometric direction-finding, TDOA geolocation, or related passive geolocation methods, including practical knowledge of their failure modes and accuracy limitations
  • 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:

  • Professional certifications in data science, signal processing, or related technical fields. Advanced academic credentials (PhD, MS) in a relevant quantitative discipline are strongly preferred and may substitute for certifications.

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.


Employment Type: FULL_TIME