Quantitative Engineer

Job Description:

Job Title:

Quantitative Engineer

Corporate

Title:

Up to Vice President

Location:

Bromley

At the company, we are guided by a common purpose to help make financial lives better through the power of every connection. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities, and shareholders every day.

One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We're devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.

the company believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization.

Working at the company will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us!

Join our bustling Bromley office, situated in one of London's greenest boroughs. Here you'll find plentiful and easy commuting routes, with central London just 15 minutes away by train.

Quantitative engineers in Global Risk are responsible for designing and implementing common, reusable, and scalable software components. These components enable GRM's data and analytical capabilities. These components can be domain independent (e.g., generic data quality tools over trillions of rows of data) or domain specific (e.g., classification models for surveillance or testing framework for Global Markets processes). Quantitative engineers work with modelers, risk managers, and technologists to understand the current state and design the future state of data and analytics.

Quantitative engineers have a combination of software engineering, big data, and modelling skills and the ability to work across the entire spectrum of a big data stack - from data to logic to model to UI to UX.

• Applying quantitative methods to develop capabilities that meet line of business, risk management and regulatory requirements Understanding financial data: schemas, flow, size, data issues, data controls, etc. Building performant big data pipelines Use programming skills and knowledge of software development lifecycle principles to deliver high quality code for model and testing processes Collaborate with key stakeholders across the Bank to understand modelling and testing business processes and requirements Think outside the box of current industry standards to develop innovative approaches Maintaining and continuously enhancing capabilities over time to respond to the changing nature of portfolios, economic conditions and emerging risks Source and evaluate data required for modelling and testing Design and develop and implement models and tests Produce clear, concise and repeatable technical documentation models and tests for internal and regulatory purposes

• Candidates should meet all or a subset of the following technical skills:
  Software engineering: modular code, software lifecycle processes, unit testing, regression testing Big data: distributed computing paradigms (e.g., mapreduce, data frames, etc), optimizing distributed software Modelling / quantitative: basic modelling techniques (regression, classification, clustering, etc)

• Bachelor's degree in Computer Science, a closely related field, or a degree from a program where software engineering was a key focus or equivalent work experience Several years relevant professional experience or evidence of personal projects and endeavours that show a passion for coding and problem solving. Strong Programming skills (e.g., Python) and solid understanding of Software Development Life cycle principles

Candidates should have at least one of these following skills and preferably have at least two of these skills:

• Strong analytical and problem-solving skills Experience applying quantitative methods such as modelling, data analytics, machine learning, and statistics to develop business solutions Experience with large scale data sets with structured or unstructured data Experience in building user facing applications over large amounts of data using technologies like React, Angular, JavaScript etc. Experience implementing process improvements and automation Strong Python development skills (including Pandas and related data-processing libraries).
  
  Experience with big data technologies such as Spark, PySpark, Hadoop, and Hive Exposure to quantitative modelling or financial modelling is a plus but not required.

• Global Risk Management experience

• At the company, we strive to prioritise employees' health and wellbeing - it's what makes us a…