Data Scientist

About the Position

Data Scientist

Lisbon

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 Acer, Gucci, Lorna Jane, GoPro, 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.

Responsibilities

• 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 Computer Science, Mathematics, Statistics, or a related field.
• 3+ years of proven experience designing and implementing machine learning algorithms and successfully deploying them to production.
• Strong understanding and practical experience with various machine learning algorithms.
• Proficiency in Python, 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.
• Proficiency in data visualization libraries, 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 environment.

Nice to Have

• Experience in the fraud domain.
• Experience with Airflow, CircleCI, PySpark, Docker, and K8S.

We Offer

• Base Salary: €60,000 - €70,000 gross annually for candidates based in Lisbon.
• Bonus Target: All full-time regular employees receive a bonus target.
• Stock-Based Awards: Eligible to receive stock-based awards.
• Benefits Package:
  • Hybrid mode of work
  • Flexible schedule
  • Healthcare benefits
  • Fully-stocked kitchens
  • Monthly benefits package-per your choice, e.g., work-from-home equipment, gym membership, wellbeing activities, and more.
  • Wellness program
  • Celebrations and activities
  • Team events
  • Happy hours
  • Awesome Riskified gifts and swags
  • Volunteer programs
  • Personal development
  • Global onboarding
  • Role-based technical skills training
  • Full access to Udemy

About the Company

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.

In the News

• C-Tech: We need to find the balance between leveraging innovative AI solutions and using them cautiously.
• Built In: How We Built This: A Riskified Technologist Unpacks The Company’s Beacon Technology.
• Globes: Riskified is among Israel’s fastest growing companies.
• Yahoo: Riskified Earns "Top Rated" Award Across Four TrustRadius Solution Categories.