At a Glance
- Tasks: Design and implement advanced data science techniques to drive business transformation.
- Company: Join JPMAM, a leader in asset and wealth management with a focus on innovation.
- Benefits: Competitive salary, professional development, and a collaborative work environment.
- Other info: Dynamic team atmosphere with opportunities for continuous learning and growth.
- Why this job: Make a real impact by applying cutting-edge data science in finance.
- Qualifications: Experience in NLP, LLM, and ML; CFA pursuit is a plus.
The predicted salary is between 60000 - 80000 £ per year.
JPMAM Data Science is dedicated to enhancing and streamlining every stage of the investment process, from financial analysis and portfolio management to client services and advisory. We analyse extensive collections of data including financial documents, analyst reports, news articles, meeting notes, and client communications to empower data-driven decision making and process automation. We are seeking passionate data scientists who can apply the latest methodologies to generate real-time and actionable insights.
The candidate must excel in working in a highly collaborative environment together with the business stakeholders, technologists, and control partners to deploy solutions into production. A strong passion for machine learning is essential, along with a commitment to continuous learning, research, and experimentation with new innovations in the field. Candidates should possess a solid understanding of modern NLP and/or financial knowledge, hands-on implementation experience, strong analytical thinking, and a keen interest in applying advanced analytics to solve complex problems in finance and asset management.
Job Responsibilities
- Design and implement advanced techniques such as semantic search, retrieval-augmented generation (RAG), named entity recognition (NER), prompt engineering, and personalization for content extraction, search, question answering, reasoning, and recommendation.
- Develop LLM, NLP, and ML solutions that address client requirements and drive business transformation.
- Work closely with partner teams—including Business, Technology, Product Management, Strategy, and Business Management—to deploy and scale developed models in production environments.
- Build comprehensive testing setups to evaluate model performance and ensure efficacy and reliability.
- Communicate results effectively to business stakeholders through written reports, visualizations, and presentations.
- Stay current with the latest research in LLM, ML, and data science, and proactively identify and leverage emerging techniques to drive ongoing enhancement.
Qualifications, Capabilities, and Skills
- Proven experience applying NLP, LLM, and ML techniques to solve high-impact business problems.
- CFA designation or current pursuit of the CFA is highly desirable.
- Proficiency in programming languages such as Python and familiarity with machine learning libraries and frameworks.
- Excellent communication skills and ability to work collaboratively in a fast-paced, dynamic environment.
- Strong analytical skills with an understanding of financial markets and asset management.
Data Scientist within Asset & Wealth Management (Senior Associate) in Glasgow employer: Jpmorgan Chase & Co.
JPMorgan Asset & Wealth Management is an exceptional employer that fosters a collaborative and innovative work culture, where data scientists are empowered to leverage cutting-edge methodologies to drive impactful solutions in finance. With a strong commitment to employee growth, the company offers continuous learning opportunities and encourages experimentation with the latest advancements in machine learning and data science. Located in a vibrant financial hub, employees benefit from a dynamic environment that promotes teamwork and the sharing of ideas, making it an ideal place for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist within Asset & Wealth Management (Senior Associate) in Glasgow
✨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 Jpmorgan Chase & Co.!
✨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 Data Scientist within Asset & Wealth Management (Senior Associate) at Jpmorgan Chase & Co..
✨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 Jpmorgan Chase & Co..
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist within Asset & Wealth Management (Senior Associate) at Jpmorgan Chase & Co., 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 Data Scientist within Asset & Wealth Management (Senior Associate) in Glasgow
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 Jpmorgan Chase & Co., 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 Jpmorgan Chase & Co.. 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 Jpmorgan Chase & Co.
✨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 Jpmorgan Chase & Co.!
✨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.
