JPMorgan Strategy & Transformation - Applied Artificial 

United States, Texas, Plano 

587080919

As a Applied Artificial Intelligence- Machine Learning- Senior Associate, on the Instrumentation & Metrics (I&M) team, you are in integral part of the team that will be responsible for leveraging your expertise in data science; machine learning to develop and maintain production grade models using various analytical techniques. You will provide ad-hoc analytics support to the Payments organization, transforming complex data into actionable insights. Additionally, you will guide the team on best practices and techniques in data science; machine learning, ensuring the effective use of data to drive business decisions.

The

Job responsibilities

• Designs, develops, and deploy machine learning models in production environments
• Utilizes Python and machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, … to develop models
• Identifies and selects appropriate features to improve model predictions
• Performs data preprocessing and feature engineering to prepare datasets for model training
• Address machine learning challenges with strong analytical and problem-solving skills
• Communicates complex machine learning concepts and results effectively to diverse audiences across various levels of the banking organization, including those unfamiliar with advanced machine learning techniques
• Participates in training sessions and workshops to enhance skills and knowledge
• Research and implementation of state-of-the-art techniques to improve model performance

Required qualifications, capabilities, and skills

• Bachelor’s or Master’s degree in machine learning, artificial intelligence, statistics, mathematics, data science, or a closely related technical field, with 4+ years of hands-on experience in machine learning
• Demonstrated expertise in machine learning algorithms, model development, and deployment. Proven track record of building and implementing machine learning models in production environments
• Proficiency in Python, with extensive experience using machine learning frameworks and libraries such as TensorFlow, PyTorch, and Scikit-learn. Familiarity with ML-specific tools and platforms like MLflow, or similar
• Ability to perform model optimization, hyperparameter tuning, and evaluation using techniques such as cross-validation, A/B testing, and performance metrics analysis
• Problem-Solving Skills: Strong analytical and problem-solving skills specifically related to machine learning challenges, including data preprocessing, feature engineering, and model selection
• Excellent written and verbal communication skills to effectively convey complex machine learning concepts and results to both technical and non-technical stakeholders

Preferred qualifications, capabilities, and skills

• Familiarity with the financial services industry and its specific machine learning applications
• Experience in natural language processing (NLP) and advanced analytics techniques relevant to machine learning
• Understanding of financial products and services, including trading, investment, and risk management, with a focus on machine learning applications