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Quant Developer Remote Jobs in Arizona (NOW HIRING)

USAA

Data Scientist Senior

Phoenix, AZ · On-site +1

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... Science, Engineering, or quantitative field; OR 4 years of relevant education and/or experience.

USAA

Data Scientist Senior

Phoenix, AZ · On-site +1

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... Science, Engineering, or quantitative field; OR 4 years of relevant education and/or experience.

JLL

Vice President, Business Development

Phoenix, AZ · Remote

This will be a remote position with travel as needed to secure business. Position Overview The ... Asset Validation (Reliability Engineering/Optimized Data Standard) * Facility Database Services

Circle

Lead KYC Analyst

Phoenix, AZ · Remote

Enterprises, financial institutions, and developers use Circle to power trusted, internet-scale ... S. degree; quantitative or technical degree a plus * CAMS, CFCS or CFE certification is a plus.

Circle

Senior Analyst, AML Know Your Customer

Phoenix, AZ · On-site +1

$97K - $127K/yr

Enterprises, financial institutions, and developers use Circle to power trusted, internet-scale ... A./B.S. degree; quantitative or technical degree a plus Circle is on a mission to create an ...

Circle

Lead KYC Analyst

Phoenix, AZ · Remote

Enterprises, financial institutions, and developers use Circle to power trusted, internet-scale ... S. degree; quantitative or technical degree a plus * CAMS, CFCS or CFE certification is a plus.

Circle

Senior Analyst, AML Know Your Customer

Phoenix, AZ · On-site +1

$97K - $127K/yr

Enterprises, financial institutions, and developers use Circle to power trusted, internet-scale ... S. degree; quantitative or technical degree a plus. * 4+ years of relevant experience in AML and ...

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Quant Developer Remote information

What are some typical challenges Quant Developers face when working remotely, and how can they overcome them?

Quant Developers working remotely often encounter challenges such as coordinating with globally distributed teams, maintaining effective communication with traders and researchers, and ensuring secure access to sensitive financial data. Overcoming these challenges involves leveraging collaboration tools, establishing clear communication protocols, and adhering to robust cybersecurity practices. Regular virtual meetings and comprehensive documentation also help maintain alignment and workflow efficiency within the remote quant team.

What are the key skills and qualifications needed to thrive as a Quant Developer in a remote setting, and why are they important?

To thrive as a Quant Developer remotely, you need strong quantitative analysis, programming expertise (especially in Python, C++, or Java), and a background in mathematics, statistics, or finance, often supported by an advanced degree. Familiarity with financial modeling tools, version control systems like Git, and cloud-based collaboration platforms is essential. Exceptional problem-solving skills, self-motivation, and effective communication are key soft skills for excelling in a distributed team environment. These abilities enable accurate model development, seamless remote collaboration, and timely delivery of complex financial solutions.

What is the difference between Quant Developer Remote vs Quant Analyst Remote?

AspectQuant Developer RemoteQuant Analyst Remote
Required CredentialsDegree in Math, Finance, or Computer Science; programming skills (Python, C++, SQL)Degree in Finance, Economics, or Math; strong analytical skills; some programming knowledge
Work EnvironmentCollaborates with developers and traders; coding-focusedAnalyzes data and market trends; supports trading strategies
Employer & Industry UsageFinancial firms, hedge funds, asset managersFinancial institutions, hedge funds, investment firms
Common Search & ComparisonOften compared for technical roles in quant teamsRelated but more analysis-focused

While both roles operate within the finance industry and require quantitative skills, Quant Developer Remote primarily focuses on coding and developing trading algorithms, whereas Quant Analyst Remote emphasizes data analysis and strategy support. Understanding these differences helps candidates target their job search effectively.

What are Quant Developers?

Quant Developers, or quantitative developers, are specialized software engineers who design, build, and maintain complex financial models, trading algorithms, and analytical tools for financial institutions. They work closely with quantitative analysts (quants) to implement mathematical models into code, often using programming languages like Python, C++, or Java. When working remotely, Quant Developers collaborate with teams via digital communication tools and are responsible for ensuring code quality and optimizing performance to support trading and risk management strategies.
What are the most commonly searched types of Quant Developer jobs in Arizona? The most popular types of Quant Developer jobs in Arizona are:
What are popular job titles related to Quant Developer Remote jobs in Arizona? For Quant Developer Remote jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Quant Developer Remote jobs in Arizona look for? The top searched job categories for Quant Developer Remote jobs in Arizona are:
What cities in Arizona are hiring for Quant Developer Remote jobs? Cities in Arizona with the most Quant Developer Remote job openings:
Quant Developer Remote jobs near you

Principal AI Data Scientist

MSR Technology Group

Phoenix, AZ • Remote

Full-time

Re-posted 29 days ago

Job description


Infomatics is partnered with a large retailer that is hiring a Principal AI Data Scientist on a direct hire/FTE basis near Phoenix, AZ. Can work remote. All applicants must be eligible & willing to be hired on W2.

You will lead various AI efforts involving computer vision, deep learning, and nlp in addition to other machine learning model builds. You will not only work on large scale projects to provide value to the customers but are also routinely involved in building our internal R&D capability to have an edge in the analytics industry. You will lead some of the most strategic and very complex problems.
Duties/Responsibilities:
  • Builds and validates machine learning models of high risk/reward problems utilizing large scale data from multiple data sources and methodologies.
  • Uses machine learning techniques to create data-driven solutions for various business use-cases.
  • Writes programs utilizing existing libraries and methodologies.
  • Interprets, communicates, and presents analytic results to C-Level executives and below.
  • Consistently collaborates with fellow data scientists, data engineers, business partners, project managers, cross-functional teams, key stakeholders, and other domains to drive business value.
  • Leads AI best practice sharing opportunities and knowledge of industry trends and innovations in data science.
  • Leads projects with external partners and vendors to develop solutions to meet business needs while resolving any issues that may arise.
  • Contributes to the organization's data strategy and roadmap.
  • Embeds and drives the organization with the most up-to-date AI methodology.
Qualifications:
  • Master's or PhD degree in a quantitative field with 5+ years of data science experience.
  • Applied expertise in artificial intelligence with experience applying natural language processing, computer vision (image processing), and deep leaning. Need to have the capability to leverage current mature mainstream AI application tools and methodology
  • Proficiency in machine learning with familiarity and actual applications of scikit-learn library machine learning techniques such as decision tree, gradient boosting, XGBoost, etc. for regression, classification, or segmentation problems.
  • Programming expertise in Python with familiarity with cloud environments (AWS, Databricks, etc.)
  • Ability to work with large data sets from multiple data sources
  • Ability to communicate complex analytics concepts and techniques to C-Level executives and below
  • Ability to work collaboratively with other data scientists, data engineers, multiple stakeholders across the business, and with external partners
  • Intellectual curiosity, a passion for data, and a results orientation.