Compliance - Quant Analytics Manager – Vice President
New York, NY, United States
JPMorgan Chase & Co.
Bring your expertise to JPMorgan Chase. As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class.
As a Data Scientist in the Compliance, Conduct Operational Risk Data Analytics team. you will be responsible for devising and developing Proofs of Concept (POCs) and deployable models using AI/ML techniques, algorithms and other statistical and numerical methods. You will need to able to extract and work with large volumes of data (both structured and unstructured) from multiple sources, transforming it into an analysis-ready format to develop the data pipeline. Additionally, you are expected to independently formulate methodologies, and quantitative and analytical tasks, from business problems.
Job Responsibilities
- Analyze complex/unstructured data to understand the business problem and use case
- Analyze business requirements, design, and develop appropriate methodology
- Develop deployable, scalable and effective models/ analytical methods as part of technology managed system or as a self-served application of a business user
- Work collaboratively and creatively with other data scientists, technology partners, risk professionals, model validation teams, etc.
- Prepare technical documentation of quantitative models for internal model risk and governance review
Required qualifications, capabilities, and skills
- 6+ years of related experience in Python, R or Scala with Bachelor of Science degree in Computer Science, Physical Sciences, Econometrics, Statistics, or other any quantitative discipline.
- Demonstrable theoretical and application knowledge of Machine Learning methods, and/or Statistical Models
- Demonstrable hands-on experience and familiarity with any or all of the following packages, algorithms, and/or alternatives, including Graph Learning Packages : (NetworkX, Torch-Geometric, Graphframes, Graphistry),ML Packages (Pandas, Scikit-Learn, XGBoost, catboost, lightgbm, automl, Optuna, Hyperopt), Visualization Packages (Matplotlib, Seaborn, Geopandas), Algorithm (Ensemble Louvian / Hierarchical Clustering, Label Propagation, Connected Component Analysis, Graph Neural net (Graph Attention Network), Page Rank, Centrality Analysis, Tree based Analysis, Outlier Detection Methods, Zero Shot/ Few Shot learning)
- Demonstrable experience with graph analytics, graph-based learning, and graph representation/visualization
- Experience in graph Database: TigerGraph, Neo4j
- Experience in Query Language: Hive, Cypher (Graph Query Language)
- Hands-on professional experience in software development especially with analytical & computationally intensive systems, digital transformations leveraging cloud technologies (AWS, GCP, Azure, Databricks etc.)
- Experience in developing and operationalization of data pipelines
- Familiarity and experience of assimilating large amounts of data from multiple databases and utilize them for creating actionable outcome; Adhering to a standardized analysis and project methodology; and Documenting quantitative analysis
Preferred qualifications, capabilities, and skills
- Post graduate degrees such as Master’s Degree, PhD, etc. is preferred
- Working knowledge of C/C#/C++ or others is a plus
- Real life exposure to Agile SDLC, ModelOps and /Or Design Thinking is desirable.
- Familiarity with Natural Language Processing techniques is a plus
- Self-starter and strong influencing skills with strong communication skills
- Experience in financial services industry and/ or, experience with process, controls and governance of a highly regulated environment
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 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 is an Equal Opportunity Employer, including Disability/Veterans
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile AWS Azure Banking Clustering Computer Science Data Analytics Databricks Data pipelines Econometrics GCP LightGBM Machine Learning Matplotlib Neo4j NLP Pandas PhD Pipelines Python R Scala Scikit-learn SDLC Seaborn Statistics Unstructured data XGBoost
Perks/benefits: Career development Competitive pay Health care Wellness
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.