Senior Data Scientist - Financial Services

Before applying, please note that this role requires permanent residency or U.S. citizenship due to the client’s government-related projects. Additionally, this is a W-2 contract position and is not open to C2C or other contracting arrangements.

7-Month Contract

Pay Rate: Negotiable Based on Experience

We are hiring on behalf of a leading company in the payment solutions industry that uses advanced AI and machine learning to drive innovation in fraud detection, risk modeling, and customer personalization. They are expanding their data science team and seeking a highly skilled Senior Data Scientist on a contract basis.

About the Role

This role is ideal for a technically strong, product-focused data scientist with proven experience deploying machine learning models at scale. The successful candidate will collaborate closely with product and engineering teams to build impactful AI solutions that improve business outcomes.

Responsibilities

• Design, build, and deploy machine learning and deep learning models for use cases such as fraud detection, recommendation systems, NLP, computer vision, and time-series forecasting
• Apply deep learning techniques including CNNs, RNNs, LSTMs, and Transformers
• Develop scalable pipelines for data preprocessing, model training, inference, and monitoring
• Lead MLOps practices including model deployment, performance tracking, and retraining
• Mentor junior data scientists and contribute to technical discussions
• Communicate complex findings effectively to technical and non-technical stakeholders

Requirements

• Bachelor’s degree in Computer Science, Statistics, Applied Mathematics, or related field; Master’s or PhD preferred
• 5+ years of industry experience in applied machine learning, with at least 2 years focused on deep learning
• Proficiency in Python and ML libraries such as scikit-learn, XGBoost, TensorFlow, Keras, or PyTorch
• Experience working with financial services or fintech data is highly desirable
• Familiarity with cloud platforms (AWS, GCP, Azure), containerization, and model serving technologies
• Strong communication skills and experience working cross-functionally