Data Lead

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:

Our data team is responsible for the management of our data assets and driving business benefit from them. You will be working alongside our front-end team who work with these data assets to deliver value to customers in an attractive, informative fashion.

In terms of tech, we primarily use Microsoft Azure components. The future tech landscape is for the team to shape - we expect to explore NLP in the near future.

Responsibilities

• Data Ingestion – interpreting results using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex mining.
• NLP/Matching - engine development, primarily with Python
• Data insights – identification and development of new data insights (data mining and visualisation, power bi, r, python). Conduct novel research in given topic areas. Present your results in a clear manner.
• Identifying areas where ML algorithms can be coupled with business logic for process automation, defining success criteria for these solutions and implementing them

Requirements

• You hold a PhD, Masters or equivalent in a quantitative field and have at least eight years professional experience in data roles
• Well versed in Computational Statistics – experience with large Bayesian networks, Monte-Carlo methods and running simulations is preferred
• Experience with statistical and machine learning techniques and confidence to drive decisions on what models best suit the problem and hand
• Experience with SQL as well as experience in programming in Python, R, or an equivalent language. 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 shouldn’t be a problem for you.

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
• Share options – we like to offer our employees a stake in our success
• A company pension to help save for your future
• 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
• A laptop and home office equipment – whatever you need to do your best work
• Hybrid working options. We currently we have offices in Farnborough and Central London.
• Regular company events and socials – we call these events InterfAcin
• 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.