About Us

Riskified empowers businesses to unleash ecommerce growth by taking risk off the table. Many of the world's biggest brands and publicly traded companies selling online rely on Riskified for guaranteed protection against chargebacks, to fight fraud and policy abuse at scale, and to improve customer retention. Developed and managed by the largest team of ecommerce risk analysts, data scientists and researchers, Riskified's AI-powered fraud and risk intelligence platform analyzes the individual behind each interaction to provide real-time decisions and robust identity-based insights. Riskified is proud to work with incredible companies in virtually all industries including Wayfair, Acer, Gucci, Lorna Jane, Go Pro, and many more.
We thrive in a collaborative work setting, alongside great people, to build and enhance products that matter. Abundant opportunities to create and contribute provide us with a sense of purpose that extends beyond ourselves, leaving a lasting impact. These sentiments capture why we choose Riskified every day.

Our Data Science and ML Eng Teams

• 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, Datalake, Databricks), Cloud operations (Docker & Kubernetes), Workflow orchestration (Airflow), and Machine Learning Platforms (Databricks & Kubeflow), coding mostly in Python, Scala, and R.
• We're a friendly, fun and diverse team. We're passionate about making data-driven decisions, and 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

In this role, you'll merge production-grade software engineering, data engineering, data science expertise and MLOps proficiency, leading the development and implementation of advanced analytical solutions for real-world applications. Your focus will be on constructing the infrastructure for the training of the company's machine learning models - from both computational aspects and analytical validity. Through collaboration with cross-functional teams, you'll integrate these ML capabilities seamlessly into our product ecosystem, driving efficient, data-driven outcomes.

What You'll Be Doing

• Lead and develop a high-performing team, fostering individual growth and collaboration.
• Develop advanced analytical solutions while bridging the gap between data science and the engineering world: transforming complex data science concepts into practical, scalable solutions.
• Build scalable ML infrastructure and pipelines for efficient data processing and model deployment. Evaluate architecture solutions based on cost, business needs, and emerging technologies.
• Manage and mentor ML engineers, ensuring their professional development and effectiveness.
• Monitor application health, set and track relevant metrics, and implement effective maintenance strategies.
• Stay abreast of industry methodologies, explore new technologies, and champion their adoption within the team.
• Advocate for improvements, scaling, and extension of ML tooling and infrastructure.
• Foster a culture of innovation, collaboration, and excellence within the ML engineering team.

Qualifications

Minimal Qualifications:

• 3+ years leading and managing a team of 3-6 engineers, ensuring their professional development and effectiveness.
• Experience building scalable and data intensive distributed services
• Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.
• Familiarity with tools and frameworks for orchestrating analytical pipelines (Airflow, DBT, Temporal).
• Excellent English communication skills, both written and verbal. Preferred Qualifications:
  
• Experience in leading cross functional teams and development of AI/ML products.
• Experience with cloud frameworks like AWS sagemaker for training, evaluation and serving models.
• University degree in a quantitative field.

If you are a passionate leader with a strong background in the blend of machine learning and engineering, we would love to hear from you. Join our team and lead a culture of data-driven decision-making at Riskified.

Life at Riskified

We are a fast-growing and dynamic tech company with 750+ team members globally. We value collaboration and innovative thinking. We're looking for bright, driven, and passionate people to grow with us.
Our Tel-Aviv team is currently working in a hybrid of remote and in-office work. We have recently moved to our new space in Tel Aviv - check it out here!
Some of our Tel Aviv Benefits & Perks:

• Equity for 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, yoga, pilates, functional training, 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

Geektime: Riskified Goes Public
Walla!: Happy Hour at the Riskified Offices
Geektime Insider: A look at Riskified Tel Aviv
Globes: Riskified to contribute the highest amount up to date to Tmura
Globes: Riskified is among Israel's fastest growing companies
Tech Crunch: Riskified Prevents Fraud on Your Favorite E-commerce Site
Riskified is deeply committed to the principle of equal opportunity for all individuals. We do not discriminate based on race, color, religion, sex, sexual orientation, national origin, age, disability, veteran status, or any other status protected by law.