Quant Developer (Minimum Of 5 Years Of Work Experience Needed)

As a Quant Developer at TEKsystems, your main responsibilities will revolve around coding and developing quantitative models, specifically in areas such as fraud detection and customer risk assessments. You will engage in model redevelopment for transaction monitoring, utilize API services, and conduct extensive model documentation. Collaborating with cross-functional teams, you'll analyze business requirements and translate them into technical specifications, ensuring models are effectively implemented in production.

To be considered for the Quant Developer position at TEKsystems, you need a minimum of 5 years of experience in quantitative analysis and a strong proficiency in Python and SQL. Familiarity with AML modeling is a plus, but experience in surveillance and market models can also serve as transferable knowledge. Additionally, you should possess skills in model documentation, preferably in LaTeX, and have a fundamental understanding of network analytics principles.

Key skills for a Quant Developer at TEKsystems include advanced programming abilities in Python and SQL, strong quantitative analysis capabilities, and experience with AML models. Knowledge of LaTeX is crucial for documentation purposes, as well as the capability to understand and implement complex algorithms. Adaptability to work on various workstreams, along with excellent communication and problem-solving skills, will also be essential in this role.

The work environment for a Quant Developer at TEKsystems is hybrid, allowing you to balance in-office collaboration with the flexibility of remote work. We prioritize a collaborative atmosphere where team members can share ideas and support one another. This approach not only fosters innovation but also enhances professional growth and work-life balance, making it a rewarding place to advance your career.

TEKsystems offers a robust benefits package for Quant Developers, which includes medical, dental, and vision coverage, along with critical illness and disability insurance. You also have the option to enroll in a 401(k) retirement plan with pre-tax and Roth contributions, life insurance coverage, and a health spending account (HSA). Additionally, we provide transportation benefits, an employee assistance program, and generous time off policies to ensure a healthy work-life balance.

When answering this question, provide specific examples of models you have developed or enhanced. Discuss the methodologies you used, the programming languages involved, and any measurable outcomes that resulted from your efforts, emphasizing your role as a Quant Developer.

To answer effectively, mention your systematic approach to testing models through back-testing, validation processes, and engaging with cross-functional teams for feedback. Highlight your familiarity with documentation practices, emphasizing that model accuracy is paramount in risk assessments.

Focus on your proficiency in Python and SQL, explaining how you utilize them for data analysis, model development, and implementation. If applicable, mention any experience with LaTeX for documentation or big data tools that could enhance your modeling capabilities.

Discuss your communication strategy, highlighting the importance of translating complex quantitative concepts into understandable language. Emphasize the role of collaboration in achieving effective models and how you ensure all team members understand the impact of the quantitative work on business needs.

When discussing challenges, choose an example that illustrates your problem-solving skills. Explain the issue you encountered, the steps you took to address it, and the eventual outcome. This reflects your resilience and ability to adapt as a Quant Developer.

Mention the critical factors such as data integrity, regulatory compliance, and the need for dynamic updating in customer risk ratings. Discuss how these elements influence your modeling decisions and align with business objectives, showcasing your understanding of both quantitative and operational aspects.

Express your commitment to continuous learning through professional development, attending industry conferences, and engaging with online resources. Share any specific publications, forums, or courses that keep you informed about the latest advancements and best practices in quantitative finance.

Detail any relevant projects where you utilized APIs for data retrieval or service integration in your models. Explain how these services enhanced model functionality and improved the user experience, thereby demonstrating your technical expertise and innovation as a Quant Developer.

Outline the key components of your documentation process, stressing the importance of clarity and accessibility for future reference. Mention tools like LaTeX that you use for structured documentation and how thorough documentation aids in model implementation and compliance checks.

Discuss your experience with tools or frameworks that support big data processing. Elaborate on techniques you employ to ensure data quality, optimize performance, and facilitate efficient model training, showcasing your technical skills in managing complex datasets.