Riskified

Machine Learning Engineer

3+ months agoTel Aviv, Israel

About Us

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. Check out the Riskified Technology Blog for a deeper dive into our R&D work.

 

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 ML Algorithm team is responsible for the full life-cycle of model development in Riskified. This includes defining, researching and implementing our traditional machine learning process in a fully automated fashion to enable fast and effortless model training and deployment. Additionally, the team is focused on automating increasingly complex aspects of the model configuration - dynamically setting thresholds to respond to population changes and segmenting the population in a smart fashion to improve the accuracy of each model. To enable this, we harness the latest MLOps architectures and require solid statistical foundations to ensure the quality of our products. 

Our vision is to automate much of our internal data science and analytics work through advanced algorithm and machine learning engineering, pushing Riskified’s world-class solutions to the next stage.

We are looking for a full-stack Data Scientist / ML Engineer, with a strong background both in statistical modelling and writing production code. Experience with MLOps methodologies is a big advantage.

What You'll Be Doing

  • Design, optimize and automate the full life-cycle of models in Riskified - Training, Deployment, Monitoring 
  • Collaborate with various teams within Riskified to enhance processes and expedite model development life-cycles
  • Design algorithms to optimize models’ configurations for multiple merchants and under several various constraints including dynamic population changes
  • Optimize, automate and monitor the whole model training and deployment process

Qualifications

  • At least 2 years of experience as a Data Scientist/ML engineer in the industry
  • M.Sc/Ph.D. in exact sciences/engineering disciplines
  • Ability to write clean and concise code, ideally in R or Python
  • Experienced with data science best-practices
  • Solid understanding of statistics and applied mathematics
  • Creative thinker with a proven ability to innovate through data exploration and application of advanced solutions
  • Dedication and persistence when it comes to monitoring and improving performance after deployment
  • Good communication skills, ability to clearly explain complex concepts
  • Experience writing production code - Advantage
  • Experience using Spark/Docker/Kubernetes and CI/CD - Advantage
  • Experience with Bayesian Optimization / Control systems - Advantage

Life at Riskified

We are a fast-growing and dynamic tech company with 650+ team members globally. We value collaboration and innovative thinking. We’re looking for bright, driven, and passionate people to grow with us.

COVID-19 Update: 

  • Our Tel Aviv team is currently working remotely. If anyone prefers to work in our office, we’re happy to offer an option to do so safely.
  • When the situation improves, we’re looking forward to adapting a hybrid of remote and in-office work for all our team members. We’ll be moving to a new space in TLV - check it out here
  • We’re growing at a rapid rate and have transitioned our interviews to Zoom.

Some of our Tel Aviv Benefits & Perks:

  • Equity to all employees, Keren Hishtalmut, pension
  • Private medical insurance, extra time off for parents and caregivers
  • Commuter and parking benefits
  • Team events, fully-stocked kitchen, lunch stipend, happy hours, birthday celebrations, yoga, pilates, basketball, soccer
  • Wide-ranging opportunities to volunteer and make an impact
  • Commitment to your professional development with global onboarding, skills-based courses, full access to Udemy, lunch & learns
  • Awesome Riskified gifts and swag! 

In the News

TheMarker: Riskified Jumps on NYSE Debut

Geektime: Riskified Goes Public

Calcalist: Riskified is the Most Promising Startup

Forbes: Riskified Becomes a Unicorn (Hebrew)

CTech: Riskified Raises $165M 

TechCrunch: Riskified Prevents Fraud on Your Favorite E-commerce Site

CTech: Riskified’s VP HR on Post-COVID Flexible Work Routines

Job ID: 4976219002

Perks and Benefits

  • Financial And Retirement
    • 401(k) with company matching
    • pension
    • company equity
    • performance bonus
  • Health And Wellness
    • health reimbursement account
    • health insurance
    • dental insurance
    • vision insurance
    • life insurance
    • short-term disability
    • long-term disability
    • wellness program
    • fitness subsidies
  • Office Life And Perks
    • flexible work hours
    • remote work opportunities
    • commuter benefits program
    • casual dress
    • pet-friendly office
    • happy hours
    • snacks
    • some meals provided
    • diversity and inclusion program
    • company outings
  • Professional Development
    • mentor program
    • access to online courses
    • promote from within
  • Vacation And Time Off
    • leave of absence
    • paid vacation
    • paid holidays
    • personal/sick days
    • maternity leave
    • paternity leave
    • sabbatical