At a Glance
- Tasks: Lead AI initiatives to transform business decisions and automate processes at J.P. Morgan.
- Company: Join J.P. Morgan, a global leader in financial services with a commitment to innovation.
- Benefits: Competitive salary, diverse work environment, and opportunities for professional growth.
- Other info: Collaborative team culture with a focus on diversity and inclusion.
- Why this job: Be at the forefront of AI technology and make a real impact in financial services.
- Qualifications: Experience in ML engineering and a strong background in quantitative disciplines required.
The predicted salary is between 60000 - 80000 £ per year.
hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role. All candidates should make sure to read the following job description and information carefully before applying.
Take a technical leadership position within JPMorgan's Commercial & Investment Bank, where you'll harness cutting-edge AI techniques to revolutionize business decisions and automate processes. As an Applied AI / ML Lead - Vice President - Machine Learning Engineer in the Applied AI ML team at JPMorgan Commercial & Investment Bank, you will be at the forefront of combining cutting-edge AI techniques with the company's unique data assets to optimize business decisions and automate processes. You will have the opportunity to advance the state-of-the-art in AI as applied to financial services, leveraging the latest research from fields of Natural Language Processing, Computer Vision, and statistical machine learning. You will be instrumental in building products that automate processes, help experts prioritize their time, and make better decisions. We have a growing portfolio of AI-powered products and services and increasing opportunity for re-use of foundational components through careful design of libraries and services to be leveraged across the team. This role offers a unique blend of scientific research and software engineering, requiring a deep understanding of both mindsets. The role is initially that of an individual contributor, though there will be optional opportunity for management responsibility dependent on the candidate's experience.
Job responsibilities:
- Build robust Data Science capabilities which can be scaled across multiple business use cases.
- Collaborate with software engineering team to design and deploy Machine Learning services that can be integrated with strategic systems.
- Research and analyse data sets using a variety of statistical and machine learning techniques.
- Communicate AI capabilities and results to both technical and non-technical audiences.
- Document approaches taken, techniques used and processes followed to comply with industry regulation.
- Collaborate closely with cloud and SRE teams while taking a leading role in the design and delivery of the production architectures for our solutions.
Required qualifications, capabilities, and skills:
- Hands-on experience in an ML engineering role.
- Masters degree or PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Statistics.
- Track record of developing, deploying business critical machine learning models.
- Broad knowledge of MLOps tooling - for versioning, reproducibility, observability etc.
- Experience monitoring, maintaining, enhancing existing models over an extended time period.
- Specialism in NLP or Computer Vision.
- Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.).
- Extensive experience with pytorch, numpy, pandas.
- Hands-on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.).
- Able to communicate technical information and ideas at all levels; convey information clearly and create trust with stakeholders.
Preferred qualifications, capabilities, and skills:
- Experience designing/implementing pipelines using DAGs (e.g. Kubeflow, DVC, Ray).
- Experience of big data technologies (e.g. Spark, Hadoop).
- Have constructed batch and streaming microservices exposed as REST/gRPC endpoints.
- Familiarity with GraphQL.
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.
J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI ML Lead - DocAI in Bristol
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like J.P. Morgan!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Applied AI ML Lead - DocAI at J.P. Morgan.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like J.P. Morgan.
✨Apply Directly through Our Website
When you find a suitable opening like Applied AI ML Lead - DocAI at J.P. Morgan, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Applied AI ML Lead - DocAI in Bristol
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at J.P. Morgan, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at J.P. Morgan. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at J.P. Morgan
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at J.P. Morgan!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.