Data Scientist Lead

Be an integral part  our team in Finance Technology where we are building world class AI ML solutions for Finance processes and organizations.

As a Data Scientist Lead at JPMorgan Chase within the Finance Technology which is aligned to Corporate Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job Responsibilities:

• Build and train production grade ML models on large-scale datasets to solve business use cases
• Use large scale data processing frameworks to manipulate and extract value from both structured and un-structured data.
• Use Deep Learning models like NLP, LLM and Gen AI for solving various business use cases involving summarization, forecasting and anomaly detection.
• Perform data modeling experiments, evaluating against strong baselines, and extracting key statistical insights and/or cause and effect relations.
• Create data models using best practices to ensure high data quality and reduced redundancy
• Stay current on industry trends and identify opportunities to adopt the latest methodologies into existing implementations
• Present and market proposed solutions to Sr. Business and Technology colleagues
• Work closely with the business users to identify and execute machine learning opportunities. 
• Work closely with the Team and the other technology partners on ML Ops aspects.  
• Manage a global team of Data scientists and Data engineers. 

Required qualifications, capabilities, and skills:

• Formal training or certification in software engineering concepts and 5+ years of applied experience.
• Bachelor’s Degree or equivalent experience in Computer Science, Data Science
• 12+ years of experience as a data scientist
• Experience with machine learning techniques and advanced analytics (e.g. regression, classification, clustering, time series, econometrics, causal inference, mathematical optimization, NLP)
• Experience with LLM and Gen AI. 
• Experience with Agentic workflows.
• Experience with ML languages such as Python, SQL, Scala
• Experience with statistical techniques - i.e. data mining, data transformations, text mining, data visualization
• Outstanding written/verbal communication and presentation skills
• Comfort with ambiguity and proven ability to structure problems
• Team oriented collaborator

Preferred qualifications, capabilities, and skills:

• Familiar with Financial Services
• Building ML models in a cloud environment
• Experience with Big Data Platforms such as Hadoop