IMC Trading Innovation, Technology & Agility

Describe a typical day for you. What work do you tackle, who do you collaborate with and what tech do you use?

As an engineer on the data analytics team, I work mostly with our trading teams, which consist of traders, quantitative researchers and fellow engineers. 

My team works on data-driven projects and builds software to enable scalable analysis. We use a combination of proprietary solutions, written in house, and open-source technologies like Python, Spark and Dask. We write software and features and are responsible for our own operations. 

My day usually starts with beginning-of-day ops, like checking production systems. If there are any scheduled maintenance, we make sure things run OK across systems. We tackle this as a team. I then pick up my sprint work, which includes writing code, reviewing my colleagues’ code, discussing with stakeholders, making sure my team has what is needed to make forward progress and and more. Sometimes, I will have a brainstorming session with teammates over coffee. 

IMC teams fill our calendars with fun events, like the recent month’s push-up challenge; I take part when I can. Depending on our sprint cadence, we will have team huddles, as well as sprint reviews, or sprint ceremony-style deep dives. 

Describe a project you’re working on right now. What’s the impact of this project, and what do you find rewarding or challenging about it?

One theme of my team's involvement is the streaming data analytics product area. Streaming means live. This is an important frontier for our data organization. We want our users to push the boundaries of data analysis, and we want to help them effortlessly build analytics to address problems at scale and use them to guide real-time decision making. 

Every project is unique. Some of our applications hinge on latency, others focus on scale; most of our users want both. 

What I find most rewarding is that we get to collaborate with various trading teams across the firm in order to understand the business motivation. We get to work with uncertainty and build out iterative solutions. Perhaps just as importantly, it is incumbent on us to build out software abstraction and present the solution in a way which is elegant and easy to reason with. We believe that when things are simple to use, it is easier to get right.

What’s the culture like on your team? Are there any rituals or practices that enable team members to grow their knowledge and connect with each other?

Highly collaborative and committed. The team is sizable enough that we can see how our work becomes impactful to the firm, yet agile enough that it often feels like I am working with a few friends “hacking” on fun projects. 

Our data analytics team operates in two-week sprints that conclude with a review session. During the sprint review, everyone is welcome to present any show-and-tell topics: code we wrote, bugs we fixed, math problems that motivated the code and design choices that did not work. The format can be as formal as a rehearsed presentation or as spontaneous as drawing system diagrams on the whiteboard. This works quite well and make learning fun and engaging.

What project are you most excited to work on in 2025, and what is particularly compelling about this work for you?

The project I am most excited about in 2025 is expanding our research capabilities within IMC on a global scale. This initiative will build a cutting-edge infrastructure to empower research teams to experiment freely, iterate rapidly and run workloads with confidence. By pushing the boundaries of technology, we aim to develop predictive models to solidify our competitive edge.

What excites me most is how this project challenges me to grow. Coming from a developer background, I’m eager to explore the complexities of data center infrastructure and enhance my business skills by working with vendors, navigating contracts and contributing to cost estimations — areas where I have limited experience. Additionally, I’m excited about collaborating with new colleagues. This project is a unique opportunity to contribute to transformative work while advancing my expertise and strengthening IMC’s future globally.

What does the roadmap for this project look like? Who will you collaborate with, and what challenges will you need to overcome in the process?

This project’s roadmap focuses on collaboration across teams to meet researchers’ immediate needs while anticipating future demands. Our goal is to ensure infrastructure never limits analysis, allowing researchers to focus on innovation. 

Key milestones include expanding our current compute resources to support both existing use cases and new initiatives, collaborating with stakeholders to create a flexible research strategy that adapts to shifting priorities, developing a cost model to better understand usage patterns, and exploring emerging technologies to boost productivity across both hardware and software. We also aim to simplify how researchers interact with the infrastructure, ensuring seamless access to key features that enhance performance. Additionally, establishing a robust global operational support model will ensure reliability and scalability as the system evolves.

Challenges like tech limitations, coordination and costs are inevitable, but we are well-positioned to overcome them. By fostering continuous learning, onboarding skilled talent, making data-driven decisions and maintaining open communication, we can build an infrastructure that drives global innovation.

What in your past projects, education or work history best prepares you to tackle this project? What do you hope to learn from this work to apply in the future?

At IMC, I’ve had the privilege of working with talented colleagues on both technical and non-technical challenges. My time on the data engineering team built a strong foundation in managing data at scale and supporting analysis tools that turn raw data into insights. More recently, working with research teams deepened my understanding of their workflows. I’ve gained hands-on experience with machine learning models and pipelines, tackling bottlenecks and improving runtimes to enhance overall workflow efficiencies. 

These experiences have strengthened my technical expertise and problem-solving skills while teaching me to leverage others’ knowledge. They’ve prepared me to tackle the complexities of expanding research infrastructure and shape my career. While I’ve gained insights into data center infrastructure, research use cases and project management, this project offers an exciting chance to make a broader impact. A key area I want to grow in is strategic thinking — evaluating challenges from a high-level perspective and driving meaningful change. I also hope to share knowledge, fostering a culture of collaboration and continuous growth within the organization.