Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Science Senior Associate - LLM/NLQ - Asset Management Data Analytics

JPMorganChase
City of London
3 days ago
Create job alert

Are you passionate about data science and eager to make a real impact in asset management? As an NLQ/LLM Data Scientist, you'll help transform investment processes and client experiences with innovative natural language and machine learning solutions. You'll collaborate with talented teams, continuously learn, and drive meaningful change using the latest data science techniques. Join us to advance your career and shape the future of investment management.


As an NLQ/LLM Data Scientist in the Asset Management Data & Analytics team, you will design and implement natural language interfaces that enhance decision‑making and optimize operational processes. You will work closely with business stakeholders, technologists, and control partners to deploy solutions into production. Your expertise will generate actionable insights and improve client experiences, while you stay at the forefront of data science innovation.


Job Responsibilities

  • Collaborate with internal stakeholders to identify business needs and develop NLQ solutions that drive transformation.
  • Apply large language models, machine learning techniques, and statistical analysis to enhance decision‑making and workflow efficiency.
  • Collect and curate datasets for evaluation and continuous improvement.
  • Perform data science experiments, such as building model architectures, hyperparameter tuning, and evaluations.
  • Monitor and improve model performance through feedback and active learning.
  • Work with technology teams to deploy and scale models in production.
  • Deliver written, visual, and oral presentations of modeling results to stakeholders.
  • Stay current with research in LLM, ML, and data science, leveraging emerging techniques for ongoing enhancement.

Required Qualifications, Capabilities, and Skills

  • Degree in a quantitative or technical discipline, or practical industry experience.
  • Proficient Python programming skills with production‑quality coding experience.
  • Experience working with structured and unstructured data.
  • Experience in prompt engineering and domain adaptation.
  • Understanding of foundational ML algorithms such as clustering and decision trees.
  • Ability to communicate complex concepts and results to technical and business audiences.
  • Active interest in applying ML solutions to investment management.

Preferred Qualifications, Capabilities, and Skills

  • Experience in data science roles such as data engineering, ML engineering, LLM engineering, or data analytics.
  • Proficiency with SQL and Snowflake.
  • Experience in Asset Management.
  • Experience applying NLP, LLM, and ML techniques to solve business problems such as semantic search, information extraction, question answering, summarization, personalization, classification, or forecasting.

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.


About the Team

J.P. Morgan Asset & Wealth Management delivers industry‑leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Science Senior Associate - LLM/NLQ - Asset Management Data Analytics

Data Science Senior Associate - LLM/NLQ - Asset Management Data Analytics

Data Science Senior Associate - LLM/NLQ - Asset Management Data Analytics

Data Science Senior Associate - LLM/NLQ - Asset Management Data Analytics

Data Scientist Senior Associate - AI

Applied AI ML - Senior Associate - Machine Learning Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.