Senior Data Scientist (Product)

Description:
**100% Remote**

Our client, an industry leader in financial services and money transfers, has an excellent opportunity for a Senior Data Scientist (Product) to work on a 6+ month contract. Work will be remote, candidates local to Denver preferred. The Senior Data Scientist will lead the development of machine learning and deep learning solutions that power intelligent decision-making and innovative products. This role is ideal for someone with extensive experience in building, evaluating, and deploying ML and neural network models in production environments. You'll collaborate cross-functionally to create and scale real-world AI applications that have a direct impact on users and business performance.

Due to client requirement, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Rate: $75 - $87 / hr. w2

Responsibilities:

• Design, build, and evaluate machine learning and deep learning models for classification, regression, recommendation, NLP, computer vision, and time-series forecasting.
• Apply deep learning techniques (e.g., CNNs, RNNs, LSTMs, Transformers) to solve complex, data-intensive problems.
• Lead the development of ML products, from model prototyping through production deployment, performance monitoring, and continuous improvement.
• Select appropriate architectures and hyperparameters, optimize model performance, and use proper evaluation metrics (e.g., AUC, F1, BLEU, IoU, perplexity) based on the use case.
• Collaborate with product managers and engineers to translate business challenges into deployable solutions using AI/ML.
• Design automated pipelines for data preprocessing, feature engineering, training, and inference (batch or real-time).
• Evaluate model drift, monitor performance post-deployment, and implement retraining pipelines as part of a production MLOps system.
• Mentor junior data scientists, contribute to code reviews, and lead technical discussions across the data science and engineering teams.

Experience Requirements:

• 5+ years of industry experience in applied machine learning, with 2+ years focused on deep learning and neural network applications.
• Experience in Banking, Payments or Financial Services formulating AI data solutions that allow us to leverage our data to know our customers better and target our resources for better market penetration and focused attention and education.
• Proficiency in Python and ML libraries such as scikit-learn, XGBoost, TensorFlow, Keras, or PyTorch.
• Deep understanding of neural networks, model regularization, overfitting/underfitting prevention, and GPU-accelerated training.
• Experience with customer data enrichments.
• Proven track record of building, evaluating, and deploying machine learning models at scale in production environments.
• Experience with cloud platforms (AWS/GCP/Azure), containerization, and model serving technologies.

Education Requirements:

• Bachelor's degree in Computer Science, Statistics, Applied Math, or related field (Master's or PhD strongly preferred).