JPMorgan Lead Data Scientist 

Ireland, Dublin 

339658346

Elevate your career by working with new AI and machine learning technologies, focusing on delivering impactful solutions. We provide opportunities to help you reach your full potential, offering the support you need to achieve your career goals. The Employee Platforms technology team is excited to invest in Dublin, establishing an engineering hub focused on the growth and application of innovative technologies to enhance the experience of our 300k+ employees.

As a Machine Learning Engineer within the JPMorgan Chase team, you will design, implement, and deploy machine learning models that adhere to our global technology standards and firm governance requirements. Collaborate closely with machine learning scientists, data scientists, software engineers, and product teams to integrate and scale machine learning solutions that promote significant business impact. Your responsibilities include designing and implementing machine learning models, deploying and scaling models to production environments, fine-tuning models for optimal performance, and continuously monitoring model performance.

Job Responsibilities:

• Design and implement machine learning models in collaboration with machine learning scientists, ensuring alignment with global technology standards and firm compliance and governance requirements.
• Deploy and scale models to production environments, ensuring robustness and reliability.
• Fine-tune models for optimal performance and efficiency, addressing any issues that arise.
• Work closely with data scientists, software engineers, and product teams to integrate machine learning solutions into existing systems and workflows.
• Continuously monitor model performance, making necessary adjustments to maintain and improve accuracy and efficiency.

Required Qualifications, Capabilities, and Skills:

• Proficiency in Python.
• Experience with one or more of the following: PyTorch, MLFlow, TensorFlow, or Scikit-learn.
• Strong understanding of software engineering principles and practices, including version control, testing, and code optimization.
• Skills in data preprocessing, feature engineering, and building data pipelines. Experience with Apache Spark, particularly PySpark.
• Experience with AWS Cloud Platform and Databricks for deploying and managing machine learning models.