Data Scientist - Borrow Analytics Manager

JPMorganChase
London
4 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist - Borrow Analytics ManagerOverview

Chase International Consumer Lending Analytics Team is the center of excellence for strategic and data analytics for International Consumer Retail and SME lending business. The team is responsible for measuring the effectiveness of and driving International Consumer Bank strategies across marketing, sales, distribution, pricing, and customer analytics. The results and learnings from these analyses, which seek to quantify both statistical and practical significance, are used to drive future strategy using a full suite of analytical techniques. The team offers significant learning and mobility opportunities for career development and future growth.

Responsibilities

  • Analyze and measure the effectiveness of lending strategies including performance of marketing campaigns or customer segmentation
  • Work with credit risk team to optimize the credit risk strategies for the lending products
  • Consult with business partners on analytical needs and make strategy recommendations
  • Solve unstructured business problems and develop deep dive analysis of customer behavior using multiple analytics and statistical techniques
  • Interpret results and present to stakeholders and senior management
  • Continuously develop skills to provide best-in-class analytics to the business

Minimum Qualifications

  • Bachelor’s and Master’s degree in a quantitative discipline (Data Science/Analytics, Mathematics, Statistics, Physics, Engineering, Economics, Finance or related fields)
  • Strong knowledge and experience in retail lending such as credit cards, personal loan, or overdraft products
  • Thought leader in data science and analytics who can define analytical agenda for projects, demonstrates ability to frame ambiguous business questions into analytical plans (e.g., assessing data needs, sourcing files, preparing data, creating new features, evaluating quality, etc.), and executes with precision
  • Knowledge of modern data mining, quantitative research, and data science techniques (e.g., decision trees, regressions, machine learning, string similarity, behavioral analytics, look-a-like models)
  • 3+ years of experience with SQL, Hive, Hadoop, Spark, Python
  • 3+ years of experience in applying statistical methods to real world problems
  • Superior written, oral communication and presentation skills with experience communicating concisely and effectively with all levels of management and partners

Successful Candidates In This Role Are

  • Self-starter with out-of-the box problem solving skills and a drive to bring new ideas to life
  • Strong time-management skills, with the ability to multi-task and keep numerous projects on track
  • Intellectually curious and eager to learn new things with an eye towards innovation
  • Strategic thinkers with the ability to focus on business goals
  • Excellent at solving unstructured problems independently
  • Highly organized and able to prioritize multiple tasks
  • Superior written and oral communication and presentation skills with experience communicating effectively with diverse audiences – across business and technology partners, including senior leadership

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. The Digital team is dedicated to creating innovative, industry-leading products and experiences that help customers access, share and control their financial data so they can make smart decisions with their money. Teams enable innovation while adhering to the firm’s data sharing principles of security, customer control and convenience, and privacy.

Job function

  • Engineering and Information Technology

Seniority level

  • Not Applicable


#J-18808-Ljbffr

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 Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.