Applied AI ML Associate Senior

Location: Hyderabad, Telangana, India

Job Family: Predictive Science

About the Role

At JP Morgan Chase, we are at the forefront of leveraging applied AI and machine learning to transform the financial services landscape. As an Applied AI ML Associate Senior in our Predictive Science team based in Hyderabad, Telangana, India, you will play a pivotal role in developing cutting-edge models that drive data-informed decisions across our global operations. This position offers a dynamic opportunity to apply your expertise in AI/ML to real-world challenges such as enhancing fraud detection systems, optimizing investment portfolios, and personalizing client experiences. Joining our team means becoming part of a collaborative environment where innovation meets impact, contributing to the bank's mission of powering the progress of individuals and communities worldwide. In this senior associate role, you will lead the design, implementation, and deployment of sophisticated ML solutions tailored to the complexities of financial data. You will work closely with cross-functional teams, including quants, data engineers, and business analysts, to translate business requirements into robust predictive models. Responsibilities include experimenting with advanced algorithms to forecast market trends, ensuring model accuracy and explainability for regulatory adherence, and scaling AI applications to handle petabyte-scale datasets from trading, lending, and wealth management divisions. Your contributions will directly influence JP Morgan Chase's competitive edge in a rapidly evolving fintech ecosystem. We value professionals who thrive in a fast-paced, intellectually stimulating setting and are passionate about ethical AI practices. This role provides exposure to state-of-the-art technologies and the chance to mentor emerging talent, fostering your growth as a leader in applied AI. With JP Morgan Chase's commitment to diversity, inclusion, and work-life balance, this position in Hyderabad offers not just a job, but a meaningful career trajectory in one of the world's leading financial institutions.

Key Responsibilities

• Develop and deploy advanced AI/ML models to enhance predictive analytics for risk assessment, fraud detection, and customer personalization in JP Morgan Chase's financial services
• Collaborate with data scientists, engineers, and business stakeholders to identify opportunities for AI-driven solutions in areas like credit scoring and market forecasting
• Analyze large-scale financial datasets using tools like TensorFlow or PyTorch to build scalable machine learning pipelines
• Conduct model validation, testing, and performance monitoring to ensure compliance with regulatory standards such as Basel III and GDPR
• Integrate AI models into production systems, optimizing for real-time decision-making in trading and investment platforms
• Mentor junior team members and contribute to the innovation of AI strategies within the Predictive Science team
• Stay abreast of emerging AI trends and technologies to drive continuous improvement in JP Morgan's financial products
• Document model methodologies and results, presenting findings to senior leadership for strategic decision-making
• Troubleshoot and resolve issues in ML model performance, ensuring robustness in volatile financial markets

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field
• 3-5 years of professional experience in applied machine learning or AI development, preferably in financial services
• Proficiency in Python, R, or Java for building and deploying ML models
• Strong understanding of machine learning algorithms, including supervised, unsupervised, and deep learning techniques
• Experience with data processing tools like SQL, Hadoop, or Spark for handling large-scale financial datasets
• Demonstrated ability to collaborate in cross-functional teams within a fast-paced environment
• Familiarity with regulatory compliance in financial AI applications, such as data privacy and model governance

Preferred Qualifications

• Advanced degree (PhD) in AI, Machine Learning, or a related field
• Prior experience at a major financial institution like JP Morgan Chase, focusing on risk modeling or fraud detection
• Certifications in AWS, Azure, or Google Cloud for ML deployment
• Publications or contributions to open-source ML projects relevant to fintech
• Experience with natural language processing (NLP) for financial text analysis

Required Skills

• Machine Learning Frameworks (TensorFlow, PyTorch, Scikit-learn)
• Programming Languages (Python, R, SQL)
• Data Processing and Big Data Tools (Hadoop, Spark, Pandas)
• Statistical Analysis and Modeling
• Deep Learning Techniques (CNNs, RNNs, Transformers)
• Cloud Platforms (AWS, Azure for ML deployment)
• Version Control (Git) and CI/CD Pipelines
• Financial Domain Knowledge (Risk Management, Fraud Detection)
• Problem-Solving and Analytical Thinking
• Communication and Presentation Skills
• Team Collaboration and Agile Methodologies
• Model Interpretability Tools (SHAP, LIME)
• Regulatory Compliance Awareness (FINRA, SEC guidelines)
• Time Management in High-Pressure Environments
• Innovation and Continuous Learning Mindset

Benefits

• Competitive base salary and performance-based bonuses aligned with JP Morgan Chase's global compensation structure
• Comprehensive health, dental, and vision insurance coverage for employees and dependents
• Retirement savings plan with company matching contributions up to 6% of eligible pay
• Generous paid time off, including vacation, sick leave, and parental leave policies
• Professional development opportunities through JP Morgan's internal training programs and tuition reimbursement
• Employee stock purchase plan and access to financial wellness resources
• Flexible work arrangements, including hybrid options in Hyderabad, with modern office facilities
• Global mobility programs and networking events within the JP Morgan Chase community

JP Morgan Chase is an equal opportunity employer.