Data Scientist - LATAM
Brazil (Remoto); São Paulo;
Signifyd leads the world in bringing the insights, innovation and compassion required to foster fearless commerce in a time of increasing digital threats. Working with some of the industry’s most recognizable retailers and brands, we are focused on using technology to enhance customer lifetime value and protect enterprises from fraud so they can focus on growing their business.
We process billions in ecommerce transactions annually through our Commerce Network of thousands of merchants selling in more than 100 countries. We focus every day on harnessing machine learning and artificial intelligence in more powerful ways to maximize our customers’ revenue and their security. None of that happens without the right people.
Our team’s strength is in its diversity and its acceptance of new ideas and new ways to look at old challenges. We are dedicated disruptors designing a new world of commerce at scale. We know humans are not one-dimensional and we celebrate the uniqueness each individual brings to the problems we solve and the culture we create.
The Data Science team at Signifyd builds the models that power our fraud detection engine. Our machine learning pipeline keeps us one step ahead of fraudsters and their constantly evolving tactics and our research and experiments develop into new products that improve the merchant payments experience.
We expect our data scientists to be hands-on. We carry solutions from a brainstorm to experimentation and all the way to deployment. We’re a varied group with a diversity of strengths -- some team members came to us from academic backgrounds, others from engineering, some from big companies and some from small, but all of us are curious and collaborative.
We are looking for someone who embodies our company values:
Curious and Hungry: Be willing to do research and design experiments by being hands-on
Tenacious: Creating something new is hard work, and our Data Scientist team never gives up
Customer Passion: Be the backbone to our platform, and help us stay ahead of fraudsters
Design for Scale: Work with the rest of the Data Science team to make fraud protection at scale possible
Agile: Some days you may spend doing research and designing experiments while others are spent using your analytical toolbox to surface insights into real-time fraud attacks.
Roll Up Your Sleeves: Partner closely internally to learn from others, and succeed as a team
How you’ll have an impact:
- Building production machine learning models that identify fraud
- Designing new algorithms that optimize all the key components of the Signifyd Commerce Protection Platform
- Writing production and offline analytical code in Python and Java
- Researching real-time emerging fraud patterns with the Risk Analysis team
- Working with distributed data pipelines
- Communicating complex ideas effectively to a variety of audiences
- Collaborating with engineering teams to continuously strengthen our machine learning pipeline
- Mentoring other members of the team
Past experience you’ll need:
- Bachelor's degree in computer science, applied mathematics, or an analytical field
- An advanced degree (M.S. or Ph.D) in computer science, applied mathematics, or an analytical field is highly preferred
- At least 3+ years of experience
- Hands-on statistical analysis with a solid fundamental understanding
- Designing experiments and collecting data
- Writing code and reviewing others’ in a shared codebase, preferably in Python and Java
- Practical SQL knowledge
- Familiarity with the Linux command line
- Fluent in Spanish
- Must be able located in CST or EST
Experience we love to see:
- Data analysis in a distributed environment
- Passion for writing well-tested production-grade code
- Using visualizations to communicate analytical results to stakeholders outside your team
- Previous work in fraud, payments, or e-commerce
Tags: Agile Computer Science Data analysis Data pipelines E-commerce Engineering Linux Machine Learning Mathematics ML models Pipelines Python Research Security SQL
More jobs like this
Explore more AI, ML, Data Science career opportunities
Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
- Open MLOps Engineer jobs
- Open Lead Data Analyst jobs
- Open Data Science Manager jobs
- Open Data Manager jobs
- Open Senior Business Intelligence Analyst jobs
- Open Data Engineer II jobs
- Open Sr Data Engineer jobs
- Open Principal Data Engineer jobs
- Open Power BI Developer jobs
- Open Business Intelligence Developer jobs
- Open Junior Data Scientist jobs
- Open Data Analytics Engineer jobs
- Open Product Data Analyst jobs
- Open Data Scientist II jobs
- Open Sr. Data Scientist jobs
- Open Senior Data Architect jobs
- Open Business Data Analyst jobs
- Open Data Analyst Intern jobs
- Open Big Data Engineer jobs
- Open Manager, Data Engineering jobs
- Open Azure Data Engineer jobs
- Open Data Product Manager jobs
- Open Data Quality Analyst jobs
- Open Principal Data Scientist jobs
- Open Junior Data Engineer jobs
- Open GCP-related jobs
- Open Data quality-related jobs
- Open Business Intelligence-related jobs
- Open ML models-related jobs
- Open Java-related jobs
- Open Data management-related jobs
- Open Privacy-related jobs
- Open Finance-related jobs
- Open Data visualization-related jobs
- Open Deep Learning-related jobs
- Open PhD-related jobs
- Open APIs-related jobs
- Open TensorFlow-related jobs
- Open PyTorch-related jobs
- Open NLP-related jobs
- Open Consulting-related jobs
- Open Snowflake-related jobs
- Open CI/CD-related jobs
- Open Kubernetes-related jobs
- Open LLMs-related jobs
- Open Generative AI-related jobs
- Open Data governance-related jobs
- Open Hadoop-related jobs
- Open Airflow-related jobs
- Open Docker-related jobs