Lead Data Scientist

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.

Join a dynamic team at the forefront of innovation in Employee Platforms. As a Data Scientist Lead, you'll revolutionize the future with cutting-edge AI and Data Science. Collaborate with a team dedicated to creating innovative, cloud-centric solutions that transform client experiences and drive industry-leading advancements. Your work will directly impact our ability to provide exceptional service to clients, keeping our services at the forefront of the industry.

As a Data Scientist Lead in Employee Platforms, you will collaborate with a team of innovators to develop AI/ML solutions. Your work will directly impact our ability to provide exceptional service to clients by delivering cutting-edge technology solutions. Engage in end-to-end software development, from design to deployment, in a fast-paced, cloud-native environment that values continuous learning and innovation.

J.P. Morgan Dublin thrives as a collaborative, tight-knit community, passionately driven by innovation, where curiosity fuels the relentless pursuit of groundbreaking ideas. The culture is centred around exploring new frontiers together by fostering an environment that encourages growth, creativity and forward-thinking.

Job Responsibilities:

• Develop and deploy machine learning models and generative AI capabilities.
• Design, code, test, and debug applications.
• Collaborate with cross-functional teams to achieve common goals.
• Keep stakeholders informed on development progress and benefits.
• Manage project lifecycle and software development deliverables.
• Solve complex problems and handle ambiguity with strong analytical skills.

Required Qualifications, Capabilities, and Skills:

• Formal training or certificate in Computer Science, Mathematics, STEM field and proficient advanced experience.
• Strong programming skills in Python and knowledge of software engineering best practices.
• Strong knowledge of basic data science libraries in Python (NumPy, pandas, scikit-learn, PySpark).
• Strong knowledge of the main deep-learning frameworks such as PyTorch, TensorFlow, Keras.
• Experience with Linux and shell scripting and experience with LaTeX.
• Solid understanding of traditional data science techniques and experience with data engineer pipelines for big data.
• Solid knowledge and hands-on experience with RNN, CNN-based models, as well as transformers.
• Ability to identify and conduct independent project work.

Preferred Qualifications, Capabilities, and Skills:

• Experience with cloud-native development and deployment; knowledge of AWS cloud services is a plus.
• Familiarity with project lifecycle and version control practices.
• Hands-on experience with graph analytics and machine learning algorithms on graphs.
• Strong ability to collaborate in a diverse, global team environment.