Riskified Data scientist
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Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
Riskified is currently hiring a Data Scientist to join their amazing team
Riskified empowers businesses to unleash e-commerce growth by taking risk off the table. Many of the worlds 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 e-commerce risk analysts data scientists and researchers Riskifieds 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.
They 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.
They 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.
About the role: The Data Science department plays a pivotal role in the company generating value to Riskified by developing algorithms and analytical production-grade solutions. They leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models NLP anomaly detection graph theory deep learning and more). As a Data Scientist you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills a solid background in statistical modeling and machine learning a technical data-savvy nature along with a passion for problem-solving and a desire to drive data-driven decision-making.
What youll be doing
- 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 companys analytical capabilities
Qualifications
- ( 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
Advantage
- Experience in the fraud domain
- Experience with Airflow CircleCI PySpark Docker and K8S
Perks & benefits
- Hybrid mode of work
- Flexible schedule
- Recharge weekends
- Healthcare & dental benefits
- Fully-stocked kitchens
- Commuter benefits
- Benefits package per monthper your choice e.g. work-from-home equipment gym membership wellbeing activities and 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
If youre ready to take on impactful challenges and excel in a collaborative forward-thinking team we encourage you to get in touch with us
Required Experience:
IC
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