Projas Technologies, LLC
AI Scientist Consumer Risk & Fraud * Direct End Client *
Projas Technologies, LLC, Sunnyvale, California, United States, 94087
We re seeking a seasoned
AI Scientist
to lead the development of advanced fraud detection and credit risk models for next-generation financial products. This role combines deep technical expertise with strategic thinking to build scalable, production-ready AI solutions that safeguard money movement systems and lending platforms.
What You ll Do
Own the
end-to-end lifecycle
of fraud risk models from design and development to deployment and monitoring.
Build
efficient data pipelines
for feature engineering, model training, scoring, and reporting using
Python and SQL .
Apply cutting-edge
machine learning techniques
(deep learning, tree-based models, NLP, time series, causal inference) to detect fraud patterns.
Collaborate with product, engineering, and risk teams to align models with business objectives and compliance standards.
Ensure
model fairness, interpretability, and regulatory compliance
in all deployments.
Research and implement innovative AI/ML approaches to improve detection accuracy and scalability.
Contribute to
MLOps best practices , including automated retraining, monitoring, and version control.
Required Qualifications
Advanced degree
(MS/PhD) in Computer Science, Data Science, AI, Statistics, or related field.
6+ years
of experience in AI/ML model development and deployment.
Strong proficiency in
Python and SQL .
Expertise in
fraud risk modeling , credit risk, and financial transaction systems.
Hands‑on experience with
ML frameworks
(TensorFlow, PyTorch) and
cloud platforms
(AWS or Google Cloud Platform).
Deep understanding of
model calibration, bias correction, and graph‑based fraud detection .
Proven ability to design
scalable pipelines
and work in agile environments.
Preferred Skills
Experience with
Vertex AI, SageMaker , or similar MLOps platforms.
Familiarity with
workflow orchestration tools
(Apache Airflow).
Strong background in
A/B testing and statistical experimentation .
Why This Role Matters You ll be solving complex, high-impact problems that protect customers and enable secure financial transactions. If you thrive in fast‑paced environments and love applying AI to real-world challenges, this is your opportunity to make a measurable difference.
AI Scientist, Machine Learning Engineer, Fraud Detection, Credit Risk Modeling, Python, SQL, TensorFlow, PyTorch, Deep Learning, NLP, Time Series Analysis, MLOps, Vertex AI, SageMaker, Apache Airflow, Big Data, Financial Risk, Cloud Computing, AWS, Google Cloud Platform, Data Pipelines, Model Deployment, Risk Analytics, Graph Analysis, Fraud Prevention, Fintech AI, Predictive Modeling, Statistical Analysis, CI/CD, Kubernetes, Data Engineering
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AI Scientist
to lead the development of advanced fraud detection and credit risk models for next-generation financial products. This role combines deep technical expertise with strategic thinking to build scalable, production-ready AI solutions that safeguard money movement systems and lending platforms.
What You ll Do
Own the
end-to-end lifecycle
of fraud risk models from design and development to deployment and monitoring.
Build
efficient data pipelines
for feature engineering, model training, scoring, and reporting using
Python and SQL .
Apply cutting-edge
machine learning techniques
(deep learning, tree-based models, NLP, time series, causal inference) to detect fraud patterns.
Collaborate with product, engineering, and risk teams to align models with business objectives and compliance standards.
Ensure
model fairness, interpretability, and regulatory compliance
in all deployments.
Research and implement innovative AI/ML approaches to improve detection accuracy and scalability.
Contribute to
MLOps best practices , including automated retraining, monitoring, and version control.
Required Qualifications
Advanced degree
(MS/PhD) in Computer Science, Data Science, AI, Statistics, or related field.
6+ years
of experience in AI/ML model development and deployment.
Strong proficiency in
Python and SQL .
Expertise in
fraud risk modeling , credit risk, and financial transaction systems.
Hands‑on experience with
ML frameworks
(TensorFlow, PyTorch) and
cloud platforms
(AWS or Google Cloud Platform).
Deep understanding of
model calibration, bias correction, and graph‑based fraud detection .
Proven ability to design
scalable pipelines
and work in agile environments.
Preferred Skills
Experience with
Vertex AI, SageMaker , or similar MLOps platforms.
Familiarity with
workflow orchestration tools
(Apache Airflow).
Strong background in
A/B testing and statistical experimentation .
Why This Role Matters You ll be solving complex, high-impact problems that protect customers and enable secure financial transactions. If you thrive in fast‑paced environments and love applying AI to real-world challenges, this is your opportunity to make a measurable difference.
AI Scientist, Machine Learning Engineer, Fraud Detection, Credit Risk Modeling, Python, SQL, TensorFlow, PyTorch, Deep Learning, NLP, Time Series Analysis, MLOps, Vertex AI, SageMaker, Apache Airflow, Big Data, Financial Risk, Cloud Computing, AWS, Google Cloud Platform, Data Pipelines, Model Deployment, Risk Analytics, Graph Analysis, Fraud Prevention, Fintech AI, Predictive Modeling, Statistical Analysis, CI/CD, Kubernetes, Data Engineering
#J-18808-Ljbffr