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JPMorganChase

Data Scientist Lead - Employee Platforms

Posted 7 Hours Ago
Be an Early Applicant
Hybrid
London, Greater London, England
Mid level
Hybrid
London, Greater London, England
Mid level
Lead the development and deployment of AI/ML solutions for Employee Platforms, managing project lifecycle and collaborating with diverse teams.
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Job Description
Revolutionize the future of Employee Platforms with cutting-edge AI and Data Science! Join a dynamic team dedicated to creating innovative, cloud-centric solutions that transform client experiences and drive industry-leading advancements.
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. Each day, you will engage in end-to-end software development, from design to deployment, in a fast-paced, cloud-native environment that values continuous learning and innovation. Your contributions will help keep our Employee Compute services at the forefront of the industry.
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
  • Bachelors or Masters in Computer Science or related field
  • 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 of RNNs, and LSTMs models

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.
  • Experience with machine learning algorithms on graphs.
  • Strong ability to collaborate in a diverse, global team environment.

About Us
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
About the Team
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.

Top Skills

AWS
Keras
Numpy
Pandas
Pyspark
Python
PyTorch
Scikit-Learn
TensorFlow

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