Riskified empowers merchants and shoppers to realize the full potential of eCommerce by making it safe, accessible, and frictionless. Our global team helps the world’s most-innovative eCommerce merchants eliminate risk and uncertainty from their business. Merchants integrate Riskified’s machine learning platform to create trusted customer relationships, driving higher sales while reducing costs. Riskified has reviewed hundreds of millions of transactions and approved billions of dollars of revenue for global brands and fast-growing businesses across industries, including Wayfair, Wish, Peloton, Gucci, and many more. As of July 29th, 2021, Riskified has begun trading on NYSE under the ticker RSKD.
Our Research Team
- We are focused on bringing value to Riskified through the development of models and analytical solutions across domains. We use a wide variety of advanced techniques and algorithms to provide maximum value from data in all shapes and sizes: classic ML and deep learning, supervised and unsupervised, NLP, anomaly detection, graph theory, and more.
- We use the most cutting-edge solutions – from event driven (Kafka), to big data solutions (Spark), Cloud operations (Docker & Kubernetes), Workflow orchestration (Airflow & Argo) and Machine Learning Platforms (Databricks & Kubeflow), working in Python and R.
- We’re a friendly, fun and diverse team. We’re passionate about making data-driven decisions, being open-minded and creative, while communicating openly and honestly. We thrive in a continuous learning culture to promote growth and remain at the forefront of technological innovation.
About the Role
The Data Sources team is responsible for exploring and leveraging the various data sources that make Riskified’s models and products possible. The team proactively explores data sources that can contribute new information and value to our models, feature engineer the raw data, and evaluates the expected value from these sources by augmenting our production models and testing for performance lift. These data sources include 3rd party vendors, open source data, our internally developed beacon and any additional information that may be provided by our customers.
The team's data scientists are experts at exploratory analysis, can quickly dig into new noisy unstructured big data that has barely been touched before, and creatively manipulate it for model improvements.
What You'll Be Doing
- Be part of a team responsible for research, analysis, model training and validations aiming to improve our products through exploiting diverse data sources
- Develop and own DS products and novel algorithms based on our beacon’s data
- Explore and analyze new and noisy data, optimize it through feature engineering methods, and evaluate its potential
- Master the online fraud prevention domain
- At least 3 years experience as a Data Scientist in the industry
- B.Sc / M.Sc in exact sciences
- Experienced with data science best-practices and machine learning algorithms
- Proficient in R or Python – functions creation, data wrangling, modelling
- Solid understanding of statistics and applied mathematics
- Experience with analyzing unstructured, big-data – advantage
- Creative thinker with a proven ability to innovate through data exploration and application of non-trivial solutions
- Good communication skills, ability to clearly explain complex concepts
To apply for this job please visit grnh.se.