Job Description:

As a Quantitative Software Engineer on the Enterprise Risk Analytics team, your main responsibilities include:

• Apply quantitative methods to develop capabilities that meet line of business, risk management and regulatory requirements

• Work effectively within and across Agile teams to design, develop, test, implement, and support high-quality software solutions across a full stack of development tools, and technologies

• Explain complex technical concepts to both technical and non-technical stakeholders

• Strong commitment to continuous learning, staying up to date with technologies, and best practices in software engineering

• Have a creative and innovative mindset, able to think outside the box to solve complex problems

• Pay attention to detail by carefully reviewing code and documentation to identify and fix issues to protect the quality and reliability of software

• Be adaptable, able to work in a dynamic environment, and adjust to changing requirements and shifting priorities

Required Skills:

• 5 years of software design and development experience using Python, PySpark/Hadoop, Pandas, NumPy, SciPy, Jupyter notebook etc.

• Experience with full Software Development Life Cycle (SDLC) including DevOps using Bitbucket/Git, Jenkins, SonarQube etc.

• Understanding of data engineering best practices related to architecture patterns supporting varying data types, volume, and velocity

• Analytical skills – Ability to troubleshoot and logically assess problems and determine solutions

• Good problem-solving skills, understanding of different data structures, algorithms, and their usage in solving business problems

• A broad knowledge financial markets, products, and risk management

• Degree in Computer Science, or other related fields (MS or PhD is a plus)

Shift:

Hours Per Week: