Data Modeler

Grow your career with an innovative global bank in Tampa, FL as a Data Modeler with expertise in big data processing, Core Java and Apache Spark particularly within finance domain. Contract role with strong possibility of extension and/or conversion. Will require working a hybrid schedule 2-3 days onsite per week. Join one of the world's most renowned global banks and trusted brand with over 200 years of continuously evolving financial services worldwide. You will work alongside some of the smartest minds in the industry who are excited to share their knowledge and to learn from you. Contract Duration: 6+ Months Required Skills & Experience • 7+ years of experience working with Big data and Data modeling. • Strong proficiency in Python and Java Spark with knowledge of core spark concepts (RDDs, Dataframes, Spark Streaming, etc.) • Java software development with at least 3 years of experience in Java Spark and Big data frameworks. • Strong experience working with financial instruments, Credit risk, and large-scale distributed computing systems. • Experience working in financial markets, risk management and financial instruments. • Familiarity with market risk concepts including VaR, Greeks, scenario analysis and stress testing. • Hands on experience with Hadoop, Spark. • Proficiency on Git, Jenkins and CI/CD pipelines. • Excellent problem-solving skills and strong mathematical and analytical mindset. • Ability to work in a fast-paced financial environment. • Experience with agentic AI tools (e.g., Devin, Claude, or Copilot) • Excellent problem-solving skills, analytical mindset, and people skills/empathetic mindset What You Will Be Doing • Will develop and optimize data pipelines for risk calculations, trade analytics and regulatory reporting. • Develop and optimize scalable Java Spark-based data pipelines for processing and analyzing large scale financial data. • Work on batch processing for credit risk analytics. • Familiarity with credit risk concepts including stress loss (GSST, CCAR) and expected credit loss (CECL, IFRS9, ICAAP) • Design and implement distributed computing solutions for risk modeling, pricing and regulatory compliance. • Ensure efficient data storage and retrieval using Big Data. • Implement best practices for spark performance tuning including partition, caching and memory management. • Design and implement distributed computing solutions for risk modeling and regulatory compliance. • Maintain high code quality through testing, CI/CD pipelines and version control (Git, Jenkins). • Work on batch processing frameworks for Market risk analytics. Posted By: Melissa Klein