Senior Associate - Data Science / Applied AI ML

JPMorganChase

Hyderabad

On-site

INR 1,800,000 - 3,200,000

Full time

30 hours ago
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Job summary

JPMorganChase Hyderabad is seeking an experienced AI/ML professional to deliver production solutions for conduct risk and compliance use cases. You will translate complex typologies into measurable model outcomes and drive innovation across supervised, unsupervised, and graph analytics.

The role emphasizes model risk management, explainability, and collaboration with RCC, Investigations, and Technology teams, with the aim of improving investigator productivity and detection accuracy.

Qualifications

  • Master's degree (or PhD) in a quantitative discipline (CS/Stats/Math/Econ/OR).
  • 4+ years hands-on AI/ML experience, preferably in financial crime / AML / risk.
  • Demonstrated experience building and deploying ML solutions with measurable outcomes.
  • Strong Python skills with PyTorch/TensorFlow and common ML tooling.
  • Knowledge of imbalanced learning, evaluation metrics, feature engineering, calibration.
  • Working knowledge of MRM expectations in regulated financial services.
  • Clear communication to explain model behavior and outputs.
  • Ability to mentor juniors through code reviews and guidance.

Responsibilities

  • Deliver production AI/ML solutions for risk & compliance use cases with measurable outcomes.
  • Advance research in supervised/unsupervised/semi-supervised learning and graph analytics.
  • Develop and enhance detection models with various ML approaches and graph analytics.
  • Manage model lifecycle: data sourcing, feature engineering, training, evaluation, calibration, monitoring.
  • Implement explainable AI and human-in-the-loop workflows for usability and precision.
  • Contribute to MLOps: CI/CD for ML, model registry, monitoring, and governed releases.
  • Support model risk management deliverables with documentation and validation.

Skills

Python
PyTorch
TensorFlow
NLP/LLM
Communication
Mentoring

Education

Master's degree (or PhD)

Tools

MLflow
Git
Docker
Kubernetes

Job description

Job Responsibilities
  • Deliver production AI/ML solutions for CCOR Conduct risk & compliance use cases by translating typologies, red flags, and control objectives into measurable model outcomes (e.g., precision/recall improvements, false-positive reduction, investigator efficiency).
  • Drive & Execute research and applied innovation in supervised/unsupervised/semi‑supervised learning, graph/network analytics, anomaly detection, and weak supervision to improve true-positive rates, reduce false positives, and enhance investigator productivity.
  • Develop and enhance detection models using supervised/unsupervised/semi-supervised approaches (e.g., anomaly detection, clustering, weak supervision) and, where applicable, graph/network analytics to identify complex patterns and relationships.
  • Execute key parts of the model lifecycle: data sourcing (with appropriate controls), feature engineering (behavioral/temporal/entity/link features), model training, evaluation, calibration/thresholding, and performance monitoring.
  • Implement interpretable ML and human-in-the-loop workflows by supporting explainability (e.g., SHAP/LIME), stable reason codes, and feedback loops with investigators to improve usability and model precision over time.
  • Contribute to MLOps and scalable deployment by partnering with technology teams on CI/CD for ML, model registry usage, automated monitoring (data drift/concept drift), and repeatable, well-governed release processes.
  • Support model risk management (MRM) deliverables by producing documentation and analysis needed for validation (assumptions, limitations, benchmarking/challengers, back‑testing, stability/drift analysis) and addressing review feedback.
  • Collaborate across stakeholders (RCC, Investigations, Operations, Technology) to align on requirements, data readiness, controls, and target operating model for sustained production support.
  • Apply GenAI/LLMs pragmatically (e.g., case narrative generation, unstructured text extraction/summarization) while prioritizing classical/statistical/graph ML methods where they deliver stronger, defensible detection efficacy.
Required Qualifications, Capabilities, And Skills
  • Master's degree (or PhD preferred) in a quantitative discipline (Computer Science, Statistics, Mathematics, Economics, Operations Research, or related).
  • Minimum 4 years of hands‑on AI/ML experience, preferably with exposure to financial crime compliance / conduct risk / AML / fraud / sanctions or similar control environments.
  • Demonstrated experience building and/or deploying ML solutions (risk scoring, anomaly detection, triage/prioritization, NLP/LLM-enablement) with a focus on measurable outcomes.
  • Strong Python skills and experience with modern ML frameworks (e.g., PyTorch/TensorFlow) and common data/ML tooling.
  • Practical knowledge of: imbalanced learning, cost-sensitive evaluation, feature engineering, model calibration/threshold optimization, and performance measurement in detection settings.
  • Working knowledge of MRM expectations (documentation, validation support, explainability, monitoring) in regulated financial services environments.
  • Clear communication skills—able to explain model behavior, tradeoffs, and outputs (including reason codes) to technical and non-technical stakeholders.
  • Ability to mentor junior team members through code reviews, pairing, and technical guidance.
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 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.

About The Team

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.

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