Senior Data Engineer, Data platform - ML Platform
Israel - Tel Aviv
Forter provides a new generation approach to meeting the challenges faced by modern enterprise e-commerce. From attracting and retaining the right shoppers by reducing friction and boosting consumer confidence across the entire purchase journey, to fighting sophisticated fraudsters and reducing chargeback losses, only Forter provides a fully automated, real-time Decision as a Service™ platform. Behind the scenes, Forter’s machine learning technology combines advanced cyber intelligence with behavioral and identity analysis to create a multi-layered detection and decisioning mechanism. Across all our client's sites, we have created a network of over 800 million buyer identities globally. Our success so far in the marketplace has allowed us to achieve a total series F valuation of over $3 Billion. Our investors include: Tiger Global, Bessemer, Sequoia Capital, March Capital, Salesforce Ventures.
About the role:
Forter is looking for a Senior Engineer with a data engineering background to join our growing ML Platform team. This is a great opportunity to enter the world of Machine Learning. Together we’ll provide tools to develop more effective models, get them into production faster and ensure that they continue to perform well over time.
ML is central to Forter’s work. In 2020 alone, it enabled us to process e-commerce transactions worth over $200B, making decisions in real time, identifying fraud rings and quickly detecting new attack methods. Precision is crucial - bad decisions by our models cost us directly, and put money into the pockets of fraudsters.
Our adoption by merchants around the world provides us with billions of fresh data points each day. Our team of data scientists, analysts and cyber intelligence specialists continually identify new signals, engineer new features and research new models. But as the volume of data and the number and complexity of models grows, so do the engineering challenges.
If this kind of working environment sounds exciting to you, if you understand that Engineering is about building the most effective and elegant solution within a given set of constraints - consider applying for this position. But hold on, you’d best check the position requirements first :)
What you'll be doing:
- Designing, building and maintaining the ML infrastructure that allows Forter’s models to make billions of real-time decisions every year.
- Handling distributed data processing pipelines to support model development.
- Acting as a consultant to researchers, data scientists and expert analysts and enabling them to research new models faster and with greater precision by providing cutting edge tooling.
- Expanding our ML infrastructure to make it scalable, quick and efficient to bring diverse models to production and to monitor their performance and drift over time.
- Expanding the pool of internal customers able to use ML at Forter. Working with them to understand their needs and help them make the most of the infrastructure that we’ll provide.
- Acting as an advocate for MLOps, continually improving our processes and raising our standards.
What you'll need:
- 2+ years experience with large scale data processing, ideally with Apache Spark.
- 5+ years developing complex software projects (Python / Ruby / Go / etc.)
- Motivation to understand the needs of internal users, provide them with great tooling and teach them how to use it.
- Experience working with public clouds (AWS / GCP / Azure)
- Fluent in written and spoken English
Projects you'll work on:
We have a ton of important work to do, which is why we’re hiring! Our projects are of course changing all the time, but here are a few that we’ve either done in the past or are planning for the near future, so you can get an idea of the types of work we do.
- Build data engineering pipelines to support ML projects and their complex data requirements.
- Develop reusable infrastructure and methodology that lets us bring new models to Production faster, without reinventing the wheel for each new business use case.
- Designing and delivering our Data Scientists’ research environment, for instance by providing experiment tracking, distributed hyperparameter search and great EDA tooling.
- Find solutions for effectively monitoring our models’ performance and context drift. Fraud prevention presents unique challenges here; most ‘ground truth’ labels arrive months after the prediction, and for transactions we decline they never arrive at all.
- Provide tools to quickly assess the impact of new features, prior to bringing them to production.
- Make it trivial for our analysts to retrain models and get the newly trained models into production.
It'd be really cool if you also:
- Have familiarity with machine learning concepts and frameworks.
- Are familiar with Databricks or Airflow.
- Are comfortable in a containerized environment.
At Forter, we believe unique people create unique ideas, and valuable experience comes in many forms. So, even if your background doesn't match everything we have listed in the job description, we still encourage you to apply and tell us why your skills and values could be an asset to us. By welcoming different perspectives, we grow together as humans and as a company.
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