Feedzai is the world’s first RiskOps platform for financial risk management, and the market leader in safeguarding global commerce with today’s most advanced cloud-based risk management platform, powered by machine learning and artificial intelligence. Feedzai is securing the transition to a cashless world while enabling digital trust in every transaction and payment type. The world’s largest banks, processors, and retailers trust Feedzai to protect trillions of dollars and manage risk while improving the customer experience for everyday users, without compromising privacy. Feedzai is a Series D company and has raised $282M to date. With a valuation of +$1.5B, the company's technology protects 900 million people in 190 countries.
The Customer Success team ensures our global customers achieve their business goals using our product. Everything you do matters: all your code, machine learning models, advisory, management, and other actions/roles will have a material impact on the way our clients run their business and how effectively we fight fraud and protect people from wrongdoing. You will be able to interact and meet many people from widely different cultures around the world and understand the business like few others. You will be able to say you protect people on a daily basis. You will be challenged with new technology, new processes, and new mindsets and will be asked to contribute to ensure continuous improvement.
Come and change the world with us.
Responsibilities:
- Understanding the data which our clients provide to us;
- Cleaning that data and validating that it is correct;
- Preprocessing the data, usually by using a mixture of shell scripts and a programming language such as Python, Java, Scala, etc
- Iteratively computing features and tuning parameters to improve the quality of the model;
- Communicating your findings to the project manager and assisting him/her in decision making on the Data Science part of the project;
- Work together with key stakeholders (data scientists, engineers, risk managers) from our clients;
- Work with other parts of the organization (Product, Research, etc.) to improve processes, best practices and tooling.
Requirements:
- MSc or PhD in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, Physics or related field;
- Proficient in Machine Learning (training and testing, avoiding overfit, etc.);
- Knowledge of Big Data technologies such as Spark, Hadoop and related;
- Proficiency in bash, Python and either Java or Scala;
- Knowledge of resource monitoring and runtime optimization (both at JVM and OS level);
- Knowledge of statistics or data visualization is a plus;
- Knowledge of tree based algorithms (Random Forests, XGBoost, LGBM) is a plus;
- Knowledge of Deep Learning algorithms is a plus;
- Ability to communicate your findings in a clear way.
#LI-IP1 #LI-remote
Your First 30-Days at Feedzai:
You will be immersed in our brand with training, connections, and one-on-one time with your manager. You may shadow your colleagues virtually or onsite at an office depending on where you work as you are supported through your Feedzai journey. In addition, you will have access to a ton of information to give you history, context, and all the knowledge you can handle about Feedzai and the team. Finally, you will start working on projects and collaborating on work currently being done. We can't wait to have you join the team!
Feedzai is an Equal Opportunity Employer and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Feedzai does not accept unsolicited resumes from recruiters or employment agencies.
Feedzai will use the personal data you provide us with by filling out this form for reviewing your application and to potentially negotiate a contract with you. Your personal data will be retained by Feedzai for 24 months following your application. Please see our Privacy Notice available at https://feedzai.com/about-us/privacy/ for more information on how we process your personal data.
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