Data Scientist, Modelling

JPMorgan Chase

Quick summary

Work type: On-site
Location: Metro Manila, National Capital Region, Philippines
Posted: 4 days ago
Nearby: 5 roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $163k

$101k most similar roles pay here $233k

This listing doesn't post a salary. Most similar roles pay $126,800–$199,387.

Based on 240 similar postings.

Employer

About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 368 open roles on FindRole.

Listed pay typically runs $152,000–$215,000 across 198 roles with salary data.

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At a glance

TL;DR · Data Scientist, Modelling

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As a Senior Associate Data Scientist in Advanced Analytics and Machine Learning at Consumer & Community Banking, you will plan and deliver analytical projects that translate complex business problems into actionable models and insights. Your day-to-day responsibilities include developing machine learning models using techniques like XGBoost, random forests, and k-means, collaborating with developers to integrate these models into existing solutions, and continuously improving model performance through automation and exploration of new data sources. You will need a strong background in statistics or computer science, experience with generative AI, proficiency in Python or R for data analysis, and intermediate skills in SQL and data visualization tools like Matplotlib or Tableau. This role is part of a team dedicated to enhancing business outcomes through advanced analytics at one of the world’s leading financial institutions.

Skills

Python R XGBoost random forest k-means SQL Matplotlib Tableau supervised learning unsupervised learning generative AI agent-based workflows retrieval-augmented generation systems

What you'll do

Plan and execute analytical projects using appropriate techniques.
Develop machine learning models that address specific business problems.
Implement models in collaboration with developers for integration into solutions.
Continuously improve model performance through evaluation and automation.
Document all aspects of model development and validation processes thoroughly.

What we're looking for

Master’s degree in statistics, computer science, engineering, or a related quantitative field
Experience with generative AI, including building agent-based workflows and retrieval-augmented generation systems
Proficiency in XGBoost, random forest, k-means algorithms, and advanced machine learning techniques
Intermediate programming skills in SQL and Python or R
Experience applying supervised and unsupervised learning methods to practical use cases
Ability to evaluate and monitor model performance using defined metrics and thresholds
Strong data visualization skills with tools like Matplotlib or Tableau

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