Senior Data Scientist


London, GB
  • Job Type: Full-Time
  • Function: Data Science
  • Post Date: 02/19/2021
  • Website:
  • Company Address: 9 East 38th St, 3rd Floor, New York, NY, 10016

About ComplyAdvantage

At ComplyAdvantage, we believe that compliance doesn’t have to be painful. Businesses need real-time financial crime insight to put them in control.

We enable you to understand the real risk of who you're doing business with, through the world's only global, real-time risk database of people and companies. We actively identify tens of thousands of risk events from millions of structured and unstructured data points - every single day.

Job Description

We are looking for a great Data Scientist to help us build our SaaS-based anti-money laundering solutions, which help organizations fight financial crime! We are building cutting edge solutions that help reveal the truth for a safer world and stop money ending up in the hands of terrorists. This is an exciting time to join us and use your ML research, modelling and engineering expertise for good as we look for creative ways to thoughtfully apply machine learning across all our products.

About Us

Who we are:

Since launching in 2014, we have been on a mission to neutralize the risk of money laundering, terrorist financing, corruption, and other financial crime on a global scale. In that time, we have raised over $88m in funding, have four global hubs located in New York, London, Singapore and Cluj-Napoca and are backed by Ontario Teachers’, Index Ventures and Balderton Capital.

We aim to grow to over 350 employees in the next 12 months, as we continue to fight the good fight against financial crime and help make compliance less painful for our client base of over 500 enterprises across 75 different countries. We're leveraging game-changing tech to help us on our mission as the financial industry’s leading source of AI-driven financial crime risk data and detection technology.

 No fight against crime is complete without the right values, and we take ours very seriously!

Focus on the Team - We're Collaborative, Human, and Humble

Kaizen - We're Curious, Proactive and Agile

Deliver Results - We're Tenacious, Accountable and Focused

We can only defeat financial crime if we have the right people with the right values in place to do so, and we're committed to investing in passionate people who are experts in their field. Our culture and working environment is second to none - Don't believe us? See what our employees have to say on Glassdoor

The role

You will join one of the Agile teams working on Adverse Information and Media, alongside our software engineers, data analysts and product team.

This team works on creating and enhancing machine learning models that look to identify individuals and organisations, and classify their actions. Your work will allow our customers to find out who has done something bad, what they did, and when.

We’re also looking for you to help us understand data problems, how to collect, clean and draw insights from the large amounts of unstructured data we deal with. As a Senior Data Scientist we’d look to you to take a lead in these discussions, bringing your own ideas as well as soliciting and incorporating ideas from others in the team.

You will advise on the best way to tackle the problem, taking ownership of the ML component in our pipeline, how to train, fine tune and evaluate the model performance in terms of quality and speed. We operate at scale, processing hundreds of articles per second.

You keep up to date with the latest research and will guide the exploration and experimentation of new SOTA machine learning methods to challenge existing solutions or to create new opportunities for us. You use your great communication and presentation skills to take everyone on the journey with you.

We pride ourselves on having an open and collaborative environment within the teams and as well as working on your own code, you will help and coach others with their work.  You will contribute to the overall success of the team, with focus on team rather than individual delivery.

Who we are looking for

We value those who take initiative and pride in their work and contribute to a positive working environment. You will be able to deliver on the points covered above, taking into account the following:

Required experience:

    Significant experience in one or more of the following areas: machine learning, recommendation systems, data mining or artificial intelligence
    Solid algorithmic and data structures knowledge, you write scalable and testable code, preferably in Python
    Experience of delivering production level ML solutions and integrating into data pipelines
    Good understanding of probability and statistics
    Extensive hands-on experience with modern ML frameworks such as Scikit-learn, TensorFlow or PyTorch
    Understanding and clarifying business problems and solving with an appropriate algorithmic solution
    Mentoring junior colleagues

Nice to have:

    Experience with feature engineering.
    Experience in solving multilingual NLP problems
    Understanding of state-of-the-art DNN models such as Attention/Transformer based models and pre-trained models
    Experience in any of the following, unsupervised machine learning techniques, coreference resolution, entity linking, knowledge graph, multitask learning.


Benefits of working at ComplyAdvantage include:

    Competitive salary
    Stock options scheme
    Unlimited time off
    Flexible working hours, and remote working opportunity
    Company Pension Scheme
    Company health care plan
    Season ticket loan
    Cycle to work scheme

ComplyAdvantage celebrates diversity in our teams, and welcomes applications from all backgrounds. Additionally, we value potential and growth, so if you don’t feel that you fulfill all of the criteria, then you should still feel comfortable to apply and your application will be considered fairly.

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Disclaimer: Local Candidates Only
This company does NOT accept candidates from outside recruiting firms. Agency contacts are not welcome.