Data Scientist Lead

Overview

We have an exciting and rewarding opportunity for you to take your Data Scientist career to the next level.

Responsibilities

• Develop and productionize high-quality machine learning models, services, and platforms to create significant technological and business impact.
• Design and implement scalable and reliable data processing pipelines, performing analysis and deriving insights to optimize business outcomes.
• Use LLMs for Generative AI applications, including text generation, classification, and question answering.
• Collaborate with cross-functional teams to identify business requirements and develop data-driven solutions using GenAI technologies.
• Build and maintain data lakes and data processing workflows using Databricks to support machine learning operations.
• Implement data visualization and analytics solutions using ThoughtSpot to provide actionable insights to stakeholders.
• Conduct research on prompt engineering techniques to enhance the performance of LLM-based models.
• Analyze and interpret complex datasets to evaluate model performance and identify areas for improvement.
• Communicate technical concepts and results effectively to both technical and non-technical stakeholders.
• Develop end-to-end ML pipelines for real-time and batch predictions and integrate them with existing applications.
• Champion a DevOps model and support the maturity of the ML development life cycle (MDLC).

Required Qualifications, Capabilities, and Skills

• Advanced degree in Computer Science, Data Science, Mathematics, or a related field.
• 8+ years of applied experience in data science, machine learning, or related areas.
• Strong programming skills in Python, with experience in machine learning frameworks such as PyTorch or TensorFlow.
• Experience in building and managing data lakes and data processing workflows using Databricks.
• Proficiency in using GenAI models (OpenAI or similar) to solve business problems and in building AI Agents and MCP Servers
• Solid understanding of data structures, algorithms, and machine learning concepts.
• Experience in NLP and deep learning, with recent exposure to prompt engineering on LLMs and with big data technologies (Hadoop, Spark, etc.)
• Hands-on experience with MLOps tools and practices, ensuring seamless integration of models into production environments.
• Experience with Enterprise Cloud infrastructure and monitoring tools like Data Dog,, Splunk, Elasticsearch, and Grafana.

Preferred Qualifications, Capabilities, and Skills

• Familiarity with data visualization tools like ThoughtSpot.
• Experience in developing APIs and integrating machine learning models into software applications.
• Knowledge of modern development technologies and tools such as Agile, CI/CD, Git, Terraform, and Jenkins.

About JP Morgan Chase

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.

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