Data Scientist - Remote

Overview

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, GoPro, and many more.

In Short

• Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
• Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
• Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
• Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
• Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
• Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
• Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
• Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities

Requirements

• B.Sc (M.Sc is a plus) in Statistics, Computer Science, Mathematics, or a related field
• 3+ years of proven experience designing and implementing machine learning algorithms and techniques in production grade
• Strong understanding and practical experience with various machine learning algorithms, such as linear regression, logistic regression, decision trees, similarity search, neural networks, and deep learning
• Proficiency in programming languages such as Python or R for data manipulation, statistical analysis, and machine learning model development
• Experience with SQL and data manipulation tools (e.g., Pandas, NumPy) to extract, clean, and transform data for analysis
• Solid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental design
• Strong analytical and critical thinking skills to approach business problems, formulate hypotheses, and translate them into actionable solutions
• Proficient in data visualization libraries (e.g., Matplotlib, Seaborn, ggplot) to create meaningful visual representations of complex data
• Excellent written and verbal communication skills to present complex findings and technical concepts to both technical and non-technical stakeholders
• Demonstrated ability to work effectively in cross-functional teams, collaborate with colleagues, and contribute to a positive work environmentAdvantages:

Benefits

• 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!