Fiserv is looking to revolutionize financial services technology to enhance client experiences by developing and maintaining cutting-edge Artificial Intelligence software applications.
Requirements
- Proficient in programming languages such as Python, Java, or Scala with extensive hands-on experience in machine learning libraries (e.g., TensorFlow, Keras, Scikit-learn).
- Strong background in machine learning fundamentals, specifically linear regression, logistic regression, support vector machines, decision trees, and neural networks.
- Demonstrated expertise in SQL and NoSQL databases for data extraction, transformation, and analysis, including the use of tools like PostgreSQL, MongoDB, or Cassandra.
- Experience with cloud computing platforms (AWS, Azure, Google Cloud) and their respective machine learning and data processing services (e.g., SageMaker, BigQuery).
- Solid understanding of parallel computing and distributed systems principles to efficiently handle large datasets and improve processing speeds.
- Ability to derive insights from data using visualization tools and libraries (e.g., Matplotlib, Tableau, Seaborn).
Responsibilities
- Architect, design, and implement scalable machine learning models and algorithms for real-time data processing and prediction.
- Develop and optimize data ingestion and transformation pipelines using tools like Apache Kafka, Airflow, and Spark to ensure high-quality feature extraction.
- Collaborate with data scientists and product engineers to transform complex business requirements into technical specifications and machine learning solutions.
- Conduct rigorous experimentation with various machine learning techniques, including supervised and unsupervised learning, reinforcement learning, and ensemble methods, utilizing frameworks such as TensorFlow and PyTorch.
- Perform hyperparameter tuning, model selection, and feature selection to enhance model performance and ensure robustness against overfitting.
- Implement and maintain version control systems (e.g., Git) for code management and documentation to ensure reproducibility and ease of deployment.
- Leverage containerization technologies like Docker and orchestration tools like Kubernetes for deploying machine learning applications in cloud environments.
Other
- 5+ years of experience in Machine learning and data science
- 3+ years of experience in deploying AI solutions in cloud
- 3+ years of experience in advanced analytics and data driven decision making
- Experience in the financial services industry
- Apply using your legal name
- Complete the step-by-step profile and attach your resume (either is acceptable, both are preferable).
