Description We are looking for a Data Scientist to join our team in Jacksonville, Florida, and deliver advanced analytics solutions that support decision-making in a financial services environment. In this role, you will transform complex data into scalable models, actionable insights, and clear visual narratives for business and technical partners. The ideal candidate brings strong experience across machine learning, big data platforms, and model deployment, along with the ability to turn exploratory concepts into production-ready solutions.

Responsibilities:

• Build, validate, and implement machine learning and predictive analytics solutions that address business needs within banking, payments, or financial services use cases.
• Prepare and refine large, complex datasets by performing data cleaning, transformation, and feature development to improve model performance and reliability.
• Develop analytical models using statistical and machine learning techniques such as classification, clustering, ensemble methods, and other predictive approaches.
• Work with big data tools and distributed processing frameworks to analyze high-volume datasets efficiently and support scalable model development.
• Create dashboards, visual reports, and data stories that communicate findings and recommendations to both technical teams and business stakeholders.
• Use Databricks capabilities such as collaborative notebooks, experiment tracking, model management, and automated workflows to support end-to-end model development.
• Design proof-of-concept initiatives that explore new opportunities, assess business value, and guide the expansion of successful solutions into broader use.
• Apply natural language processing methods where appropriate to extract insight from unstructured information and solve business problems.
• Partner with cross-functional teams to deploy, monitor, and maintain production-ready models in alignment with governance and operational expectations. Requirements
• Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or another quantitative field.
• At least 5 years of experience delivering end-to-end data science or machine learning solutions in payments, banking, or financial services settings.
• Strong programming skills in Python and experience working with technologies such as Spark, PySpark, R, Hadoop, Kafka, and ETL processes.
• Hands-on experience with data manipulation and model development tools, including Pandas, NumPy, Scikit-learn, Plotly, Matplotlib, and Seaborn.
• Advanced ability to build visual analytics and business intelligence outputs using platforms such as Tableau.
• Practical experience with Databricks, including MLflow, AutoML, Model Registry, notebook-based collaboration, and MLOps-oriented workflows.
• Demonstrated success explaining complex analytical methods and results to audiences with varying levels of technical expertise.
• Familiarity with NLP techniques, modern MLOps practices, and regulated model governance; experience with generative AI, cloud-based ML environments, or mentoring entry-level team members is a plus.

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