At a Glance
- Tasks: Apply advanced machine learning methods to tackle complex challenges in time series analysis and reinforcement learning.
- Company: Join J.P. Morgan, a global leader in financial services, known for innovation and excellence.
- Benefits: Enjoy a collaborative work environment, opportunities for learning, and a commitment to diversity and inclusion.
- Why this job: Be part of a cutting-edge team driving impactful solutions using AI and machine learning technologies.
- Qualifications: PhD in a quantitative field with hands-on experience in machine learning and deep learning tools required.
- Other info: Ideal for curious, detail-oriented individuals passionate about solving complex analytical problems.
The predicted salary is between 43200 - 72000 £ per year.
The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm's data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.
As an Applied AI ML Senior Associate in Machine Learning Center of Excellence, you will have the opportunity to apply sophisticated machine learning methods to complex tasks including time series analysis, reinforcement learning, causal inference, and natural language processing. You will collaborate with various teams and actively participate in our knowledge sharing community. We are looking for someone who excels in a highly collaborative environment, working together with our business, technologists and control partners to deploy solutions into production. If you have a strong passion for machine learning and enjoy investing time towards learning, researching and experimenting with new innovations in the field, this role is for you. We value solid expertise in Machine Learning and Econometrics with hands-on implementation experience, strong analytical thinking, a deep desire to learn and high motivation.
Job responsibilities:
- Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community.
- Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as time-series analysis and modelling, constrained optimization and prediction for large systems, prescriptive analytics, and decision-making in dynamical systems.
- Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production.
- Drive Firm wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business.
Required qualifications, capabilities, and skills:
- PhD in a quantitative discipline, e.g. Econometrics, Finance/Accounting, Mathematics, Computer Science, Operations Research.
- Ability to conduct literature research in unfamiliar fields.
- Hands-on experience and solid understanding of machine learning and deep learning methods.
- Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas).
- Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals.
- Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
- Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments.
- Curious, hardworking and detail-oriented, and motivated by complex analytical problems.
Preferred qualifications, capabilities, and skills:
- Strong background in Mathematics and Statistics and familiarity with the financial services industries.
- Solid knowledge in financial reports analysis; understand relationships among items in Balance Sheet, Income Statement, and Cashflow statement.
- Ability to develop and debug production-quality code and solid experience in writing unit tests, integration tests, and regression tests.
- Published research in areas of Machine Learning/Deep Learning/Reinforcement Learning OR Finance/Accounting at a major conference or journal.
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.
Contact Detail:
JPMorgan Chase & Co. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AI ML Senior Associate - Machine Learning Center of Excellence - Time Series Reinforcem[...]
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning, particularly in time series analysis and reinforcement learning. Attend relevant webinars or workshops to deepen your understanding and network with professionals in the field.
✨Tip Number 2
Engage with online communities and forums focused on machine learning and AI. Sharing your insights and asking questions can help you build connections that may lead to referrals or insider information about the role.
✨Tip Number 3
Showcase your collaborative skills by participating in group projects or hackathons related to machine learning. This experience will not only enhance your resume but also demonstrate your ability to work effectively in a team environment.
✨Tip Number 4
Prepare to discuss your hands-on experience with machine learning tools like TensorFlow and PyTorch. Be ready to share specific examples of projects where you've applied these technologies to solve complex problems.
We think you need these skills to ace Applied AI ML Senior Associate - Machine Learning Center of Excellence - Time Series Reinforcem[...]
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, econometrics, and any specific projects related to time series analysis or reinforcement learning. Use keywords from the job description to align your skills with what the company is looking for.
Craft a Compelling Cover Letter: In your cover letter, express your passion for machine learning and detail your hands-on experience with tools like TensorFlow and PyTorch. Mention any collaborative projects you've worked on and how they relate to the role at JPMorgan Chase.
Showcase Your Research Skills: If you have published research or conducted literature reviews in machine learning or related fields, be sure to include this in your application. Highlighting your ability to conduct independent research will demonstrate your fit for the role.
Prepare for Technical Questions: Anticipate technical questions related to machine learning methods and frameworks. Be ready to discuss your experience with model performance metrics and how you've applied these in real-world scenarios, as this will likely come up during the interview process.
How to prepare for a job interview at JPMorgan Chase & Co.
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with machine learning and deep learning toolkits like TensorFlow and PyTorch. Bring examples of projects you've worked on, especially those involving time series analysis or reinforcement learning, to demonstrate your expertise.
✨Demonstrate Collaborative Spirit
Since the role involves working with various teams, highlight your experience in collaborative environments. Share specific instances where you successfully partnered with business, technology, or compliance teams to deploy solutions.
✨Prepare for Problem-Solving Questions
Expect questions that assess your analytical thinking and problem-solving abilities. Be ready to walk through your thought process when tackling complex analytical problems, and how you would approach designing experiments or evaluating model performance.
✨Stay Updated on Industry Trends
Research recent advancements in machine learning and AI, particularly in financial services. Being knowledgeable about current trends will not only impress your interviewers but also show your passion for continuous learning and innovation in the field.