What we do at Codat

Codat helps banks, FI's and fintechs create stronger, data-driven relationships with their business customers. Our platform makes it easy for banks to access, synchronize, and interpret data from customers' financial software, enabling critical use cases such as supplier onboarding for commercial card and virtual card programs, accounting automation and underwriting business loans.

We empower the world's largest financial institutions, banks and fintechs to grow their share of wallet, reduce churn, and scale operations efficiently. Codat is backed by leading investors, including JP Morgan, Canapi Ventures, Shopify, Plaid, Tiger Global, PayPal Ventures, Index Ventures, and American Express Ventures.

Who are we looking for?

We are looking for a highly experienced and product-focused Senior Data Scientist to join our team. You will be both a leading individual contributor and a mentor, taking ownership of the delivery of high-quality, data-driven solutions to some of our most complex and ambiguous challenges. You’ll make a significant contribution to our data science stack and capability, helping to foster a team culture of technical excellence and continuous improvement. You will also play a key role in our broader engineering culture, defining best practices, collaborating with other senior engineers, and fostering a mindset of continuous improvement.

The Role

As a Senior Data Scientist at Codat you will:

• Technical Leader & Mentor: Drive excellence and foster a culture of continuous improvement. You'll act as a mentor to other team members, sharing expertise and guiding them in best practices for design, development, and support of products, while also leading technical initiatives and contributing to architectural decisions.

• Domain-Oriented Problem Solving: Go beyond the technical spec to develop a deep empathy for our clients by understanding the nuances of their connected financial data. You will use this domain expertise to contribute to product strategy, challenge assumptions, and architect solutions that deliver genuinely actionable intelligence.

• AI-Driven Innovation: Proactively identify and prototype opportunities to embed AI/ML into our core products, leveling up our offering and delivering novel value to clients. Alongside this, you will champion the use of AI tools to streamline engineering operations, enhance productivity, and upskill others across the team.

• AI-Driven Execution: Leverage AI to maximize productivity, be that in conducting research, gathering information or building solutions

• Be action-oriented: Eager to take ownership of large-scale projects, championing ideas from discovery all the way to production

• Strategic & Tactical: Balancing big-picture vision with hands-on delivery. Threading the needle between speed and quality, delivering value quickly whilst building firm foundations for our products and in-house capabilities

• Communication: Communicate technical concepts effectively to both technical and non-technical team members.

• Be a team player who loves working within a multidisciplinary team and collaborating with other teams

Codat's values - It is important that all team members live by our values.

• United - You focus on 'We' over 'Me', guiding your team and colleagues to solve problems together

• Unstoppable - ou embrace challenges, provide clarity in ambiguity and look to elevate everything around you to new levels.

• Useful - You focus on solving real problems for our customers, you consistently look to innovate and are not limited by the 'scope' of your role.

What you’ll bring to the team

• A broad and deep understanding of a wide range of data science techniques, including classic ML, deep learning and cutting edge AI & Agents, honed through extensive practical experience across a range of domains

• Expert-level proficiency in Python and its data science ecosystem (e.g., scikit-learn, pandas), with the ability to select the right tools for complex problems and set technical standards for the team

• Advanced, hands-on expertise in SQL and big data platforms like Databricks, used for sophisticated data manipulation, feature engineering, and optimizing complex data workflows

• Extensive, proven experience in MLOps: owning the end-to-end lifecycle of production models, including designing scalable and reliable deployment strategies (e.g., serverless applications, containerization) and model monitoring, observability and continuous improvement

• Strong proficiency in designing and utilizing CI/CD pipelines and cloud infrastructure (e.g., AWS, GCP, Azure) to automate and streamline the delivery of data science products, with an appreciation of wider software development best practices and how they can be applied

• Exceptional ability to articulate complex data science concepts and solutions, influencing both technical and non-technical stakeholders and shaping product strategy through clear, data-driven narratives

• An intuitive understanding why data protection and security practices are important

• A degree in a STEM subject