At ThetaRay, our purpose is to make the world a safer place by protecting the integrity of the global financial system.
We do this by putting AI at the core of both our technology and our way of working. Our AI-driven solutions help banks and fintech companies worldwide detect and stop serious financial crime, from human trafficking and terrorist financing to sophisticated money laundering, while advanced technology, automation, and AI-driven tools help our teams collaborate smarter, move faster, and continuously improve how we build, deliver, and innovate.
About the role:
We are looking for a Data Engineer to turn expertise, initiative, and bold thinking into real impact on the next generation of AI-driven financial crime detection.
If you combine strong data engineering capabilities with hands-on experience in building and optimizing data pipelines and transformations at scale, and if you are motivated by designing the data flows that power real-world money laundering detection for global financial institutions, ThetaRay could be your next challenge.
Responsibilities:
- Implement and maintain data pipeline flows in production within the ThetaRay system based on the data scientist’s design
- Design and implement solution-based data flows for specific use cases, enabling the applicability of implementations within the ThetaRay product
- Building a Machine Learning data pipeline
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader
- Work with product, R&D, data, and analytics experts to strive for greater functionality in our systems
- Train customer data scientists and engineers to maintain and amend data pipelines within the product
- Travel to customer locations both domestically and abroad
- Build and manage technical relationships with customers and partners
- 2+ years of Hands-on experience working with Apache Spark - must
- Hands-on experience with SQL
- Hands-on experience with version-control tools such as GIT
- Hands-on experience with Apache Hadoop Ecosystem including Hive, Impala, Hue, HDFS, Sqoop etc..
- Experience with Python (Pandas)
- Experience with PySpark/Scala/Java/R
- Hands-on experience with data transformation, validations, cleansing, and ML feature engineering
- BSc degree or higher in Computer Science, Statistics, Informatics, Information Systems, Engineering, or another quantitative field
- Experience working with and optimizing big data pipelines, architectures, and data sets - an advantage
- Strong analytic skills related to working with structured and semi-structured datasets
- Build processes supporting data transformation, data structures, metadata, dependency, and workload management
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
- Business-oriented and able to work with external customers and cross-functional teams
- Fluent in English & Spanish both written and spoken
Nice to have
- Experience with Linux
- Experience in building Machine Learning pipeline
- Experience with Elasticsearch
- Experience with Zeppelin/Jupyter
- Experience with workflow automation platforms such as Jenkins or Apache Airflow
- Experience with Microservices architecture components, including Docker and Kubernetes.
Skills Required
- 2+ years of hands-on experience working with Apache Spark
- Hands-on experience with SQL
- Hands-on experience with version-control tools such as GIT
- Hands-on experience with Apache Hadoop Ecosystem including Hive, Impala, HDFS, Sqoop
- Experience with Python (Pandas)
- Experience with PySpark/Scala/Java/R
- Hands-on experience with data transformation, validations, cleansing, and ML feature engineering
- BSc degree or higher in Computer Science, Statistics, Informatics, Information Systems, Engineering, or another quantitative field
- Experience working with and optimizing big data pipelines, architectures, and data sets
- Strong analytic skills related to working with structured and semi-structured datasets
- Business-oriented and able to work with external customers and cross-functional teams
- Fluent in English & Spanish both written and spoken
What We Do
At ThetaRay, we believe that banks no longer have to de-risk when they can expand their cross-border ecosystem safely. ThetaRay is the developer of SONAR, a groundbreaking, AI-powered, transaction-monitoring SaaS solution for cross-border payments that allows banks to expand their business opportunities by achieving safe and reliable cross-border payment monitorisation. ThetaRay's technology is the only packaged SaaS offering that analyzes SWIFT traffic, risk indicators, and client/payer/payee data to detect anomalies indicating money laundering activity across complex, cross-border transaction paths. It is also one of the only AI-driven AML solutions that can be easily integrated and deployed within days, with minimal implementation required. ThetaRay's solution increases detection capabilities for both supervised and unsupervised data and includes profiling and advanced analytics assessments, all in one platform. Financial organizations that rely on highly heterogeneous and complex ecosystems benefit greatly from ThetaRay's unmatchable low false-positive rates.
