Applied AIML Associate Senior Causal ML
Share
Job Location:
Monthly Salary:
Posted on:
13 hours ago
Vacancies:
1 Vacancy
Job Summary
Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team. Our team focuses on applying GenAI ML and statistical models to solve business problems in the Global Wealth Management space.
As an Applied AI/ML Senior Associate within our dynamic team in Asset and wealth Management you will apply your quantitative data science and analytical skills to complex problems. We are seeking a Data Scientist with strong foundations in causalinferencemachine learning statistical modeling and applied experimentation to help build next-generation decision systems across pricing campaign targeting and related business use cases. This role is ideal for someone who can move beyond prediction and help the organization understand cause-and-effect relationships in real-world observational settings.
Job responsibilities
Engage with stakeholders and understanding business requirements
Develop AI/ML solutions to address impactful business needs
Work with other team members to productionize end-to-end AI/ML solutions
Engage in research and development of innovative relevant solutions
Document developed AI/ML models to stakeholders
Coach other AI/ML team members towards both personal and professional success
Collaborate with other teams across the firm to attain the mission and vision of the team and the firm
Required qualifications capabilities and skills
Strong quantitative training in Statistics Data Science Economics Computer Science Applied Mathematics Operations Research ora related field.
Strong understanding of causal inference fundamentals including confounding mediation selection bias andidentificationassumptions.
Practical knowledge of techniques used tocontrol forconfounding and estimate causal effects in observational data.
Familiarity with causal reasoning concepts such as backdoor criterionfrontdoorcriterion and treatment effect estimation.
Advanced degree in analytical field (e.g. Data Science Computer Science Engineering Applied Mathematics Statistics Data Analysis Operations Research)
Experience in the application of AI/ML to a relevant field
Demonstrated practical experience in machine learning techniques supervised unsupervised and semi-supervised
Strong experience in natural language processing (NLP) and its applications
Solid coding level in Python programming language with experience in leveraging available libraries like Tensorflow Keras Pytorch Scikit-learn or others to dedicated projects
Previous experience in working on Spark Hive and SQL
Preferred qualifications capabilities and skills
Industry experience applying causal machine learning to pricing marketing campaign targeting personalization or customer analytics.
Experience with temporal causality longitudinal data panel data or dynamic treatment effects.
Experience with time series forecasting or combining causal inference with time-dependent modeling.
Familiarity with experimentation A/B testing quasi-experimental design or synthetic control methods.
Experience with modern causal ML methods such as meta-learners uplift models causal forests or double machine learning.
Financial service background .PhD/Masters
Required Experience:
Senior IC
About Company
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans ov ... View more
