Data Scientist

About us
Our product is all about collaboration and innovation. So are our people. We’re a small team, but we’ve got a big vision: to build a brand-new infrastructure for operational risk management. It’s not easy. We’re redefining the way some of the world’s biggest financial services companies and banks work with data. There are a lot of challenges – but a lot of opportunities to think and act creatively, too.
Backed by banks (JP Morgan, Citi, Barclays, Lloyds, BNP) and ratings agencies, Acin helps banks objectively manage their risk control landscape. Based on a network of peers, Acin’s data protocols connect a bank’s risk control data across their firm and industry leading to greater cost savings, and creating huge efficiency savings across the bank both in front and back-office operations.
The role
You will be responsible for identifying ways in which Machine Learning and AI can be used across the company, either to deliver more value to clients, or improve efficiency of internal processes. You will work in an intellectually curious team of data scientists, alongside front-end and back-end developers to deliver features in an attractive, informative fashion. You primarily use Microsoft Azure components. The future tech landscape is for the team to shape, but the direction of travel is state-of-the-art graph-based methods.

Main duties

Contributing towards our internal recommender system methodology, improving suggestion performance.
Improving model alignment within in our recommender system leading to a higher volume of data processing automation downstream.
Helping to identify the best graph-based AI methodology to improve machine understanding of our data.
Identifying areas where LLMs/ML can be used to extract useful insights to improve client experience.
Integrate state-of-the-art prompt engineering methods into our LLM-driven products to improve performance.
Write production-ready code to execute ML/AI pipelines efficiently, and build these into production systems
Conduct novel research in given topic areas. Results should be documented in a clear manner and presented to the team in monthly knowledge sharing sessions.
Mentor junior members of the team where requested.
Follow MLOps and LLMOps best practices set within the team and align your deliverables to it.
Continuously seek out opportunities to innovate.
Stay up to date with new AI tools and research strategies.
Requirements
Relevant experience in Data Science role.
Solid understanding of statistical and machine learning techniques and can select the models that best suit the problem and hand.
Solid understanding of the principles of a recommender system and how they work.
Experience working with unstructured natural language data and LLMs.
Experience in programming in Python. Strong skills in data analysis, data visualisation, and feature engineering.
Natural creativity with a track record of exploring innovative use cases of data and applications of statistical/ML methods.
Strong communication skills; explaining complex technical concepts to employees across the business.
Benefits
This is an exciting opportunity to join a fast-growing, dynamic fintech that is creating huge momentum in the market. Alongside a friendly, dynamic, and inclusive culture, we offer…
25 days annual leave plus bank holidays
Enhanced Private Health Insurance for you and your family
Life insurance, including access to their Smart Health services such as unlimited access to an online GP as well as a range of other health and wellbeing experts
Enhanced maternity and paternity leave policies
Perkbox - a discount platform and wellbeing resource centre.
Employee Assistance Program – access to free counselling sessions and support through Perkbox.
Cycle to work scheme
Electric Car Leasing
Hybrid working options + an amazing office in Central London
Regular company events and socials
A strong team culture where successes are celebrated together. Our core company values are get up and go, keep going, and always further.
Acin is an equal opportunity employer. We value a diverse workforce and an inclusive culture. We encourage applications from all qualified individuals without regard to race, sex, colour, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation and gender identity or expression.

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