Applied AI/ML Specialist

Applied AI/ML Specialist at JPMorganChase

JPMorganChase, a leading financial institution, is seeking an Applied AI/ML Specialist to join their team. This role focuses on leveraging advanced machine learning and deep learning techniques to address complex financial challenges, particularly in payment optimization and recommendation systems.

Job Duties

• Identify strategic and operational challenges within the financial domain that can be effectively solved through data-driven approaches.
• Apply cutting-edge machine learning and deep learning techniques to enhance payment optimization and recommendation systems.
• Formulate identified business problems into quantitative models for effective analysis.
• Develop and apply descriptive and predictive models, including linear and non-linear time series techniques, for accurate forecasting.
• Access and query diverse databases and data sources to construct comprehensive datasets for analytical purposes.
• Transform unstructured banking data into high-quality data assets to support both tactical and strategic product solutions.
• Work with highly confidential data, performing exploratory analysis to ensure data integrity by identifying missing elements and outliers.
• Combine strong business acumen with theoretical knowledge to perform feature engineering, augmenting available data for richer insights.
• Define and implement robust evaluation metrics to measure and monitor model performance effectively.
• Construct both batch and real-time model prediction pipelines, collaborating with data engineers to resolve scalability issues in testing and production environments.
• Partner with various teams, including Business Management, Technology, Product Management, and Compliance, to successfully deploy solutions into production.
• Communicate complex analytical results as quantifiable business impacts, enabling accurate risk assessment and clear explanations to senior management and stakeholders.

Qualifications

Minimum education and experience required: A Master's degree in Data Science, Operation Research, Computer Science, Mathematics, Electrical Engineering, Financial Engineering, Quantitative Finance, Computational Finance, or a related field of study, coupled with 2 years of experience in an Applied AI/ML Specialist role, Data Scientist, or a related occupation.

Skills Required

• Designing and implementing robust data analysis solutions using Python, R, and SQL to extract actionable insights from complex datasets.
• Reading, analyzing, and executing algorithms on datasets using Hadoop, PySpark, Apache Spark, and Hive for scalable and efficient processing of structured and unstructured data.
• Python-based interactive coding and experimentation using Jupyter Lab.
• Visualizing data effectively with Tableau.
• Creating detailed statistical plots with Matplotlib and Seaborn.
• Implementing version control using Git, GitHub, and Bitbucket for managing code repositories, tracking changes, and ensuring project development integrity.
• Forecasting trends, identifying seasonal patterns, and making data-driven predictions using ARIMA and SARIMA models for time series analysis.
• Quantifying relationships between variables and predicting outcomes using regression analysis techniques including Linear, Logistic, GLM, Ridge, and Lasso.
• Constructing models that categorize data based on input features, optimizing predictive accuracy using classification algorithms including Random Forest, SVM, and Decision Trees.
• Implementing ensemble methods including XGBoost, Gradient Boosting Machine, Bagging, and Boosting to aggregate models for improved performance.
• Partitioning datasets into groups based on similarity metrics and creating insights using clustering techniques including K-means, Hierarchical, DBSCAN, and Graph ML.
• Reducing feature space dimensionality and enhancing computational efficiency and model interpretability using methods including Principal Component Analysis, Singular Value Decomposition, and feature engineering.
• Extracting features from text data using NLP techniques including TF-IDF for text vectorization and POS tagging for syntactic analysis.
• Capturing semantic relationships between words using fuzzy matching for approximate string comparison and embeddings with FastText, Word2Vec, or GloVe.
• Comprehensive language processing using Python libraries including NLTK and SpaCy.
• Optimizing model performance using model evaluation techniques including cross-validation and hyperparameter tuning.
• Assessing predictive accuracy and reliability using metrics including ROC-AUC, Gini Score, and Precision-Recall.
• Designing and implementing deep learning architectures including CNNs for image processing, RNNs and LSTMs for sequential data analysis, and Transformers for advanced language modeling and attention mechanisms.
• Employing optimization techniques including hyperparameter tuning, model pruning, and gradient descent for minimizing loss functions and enhancing model performance.
• Predictive modeling using mathematical concepts including linear algebra, multivariate calculus, simulation, hypothesis testing, and probability theory and distributions.

About Us

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 over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

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.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

About The Team

J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.

Key skills/competency

• Data Analysis & Insights
• Machine Learning & Deep Learning
• Python, R, SQL
• Big Data Technologies (Hadoop, Spark)
• Model Deployment & Scalability
• Time Series Analysis (ARIMA, SARIMA)
• Regression & Classification Algorithms
• NLP & Text Mining
• Model Evaluation & Optimization
• Financial Problem Solving