- Company Name
- JPMorganChase
- Job Title
- Applied AI/ML - Senior Associate
- Job Description
-
**Job Title:** Senior Associate – Applied AI/ML Scientist
**Role Summary:**
Develop and operationalize AI/ML models and data pipelines to enhance payment processing, fraud detection, and customer experience. Partner with product, technology, risk, and compliance teams to translate business problems into scalable, high‑performing machine‑learning solutions within the payments ecosystem.
**Expectations:**
- Deliver end‑to‑end ML solutions that meet defined business success metrics (accuracy, latency, scalability).
- Ensure models comply with regulatory and risk standards, maintaining thorough documentation and performance tracking.
- Communicate model impact and technical concepts clearly to senior stakeholders.
- Lead analytical direction, turning ambiguous business questions into structured, data‑driven plans.
**Key Responsibilities:**
- Collaborate with cross‑functional teams to define problem statements and data requirements.
- Design, develop, test, and deploy ML/AI models (NLP, LLM, computer vision, classification/regression) on cloud platforms.
- Build and maintain scalable data processing pipelines (SQL, PySpark, AWS).
- Perform exploratory data analysis, feature engineering, and model evaluation.
- Document models, monitor performance, and ensure adherence to compliance and risk guidelines.
- Translate model outputs into business impact metrics and present findings to senior management.
**Required Skills:**
- Python programming; experience with TensorFlow, PyTorch, NumPy, Scikit‑Learn, Pandas.
- Proficient in Jupyter Notebook/Lab, Shell scripting, SQL, PySpark, and AWS services.
- Strong foundation in machine‑learning algorithms, neural networks, LLMs, and Generative AI.
- Expertise in NLP, LLMs, or computer vision (≥3 years).
- Advanced exploratory data analysis and statistical reasoning.
- Excellent problem‑solving, communication, and stakeholder‑management abilities.
**Required Education & Certifications:**
- Master’s degree in a quantitative discipline (Computer Science, Data Science, Mathematics/Statistics, Operations Research, or related field).
- Minimum 3 years of relevant industry experience.
**Preferred (Optional) Qualifications:**
- Experience in financial services or investment banking.
- Familiarity with Azure, Docker, Kubernetes, Databricks, Snowflake.