Research Intern – Statistics, Financial Advisor Insights

Job not on LinkedIn

October 4

Apply Now

Receive Emails with Similar Jobs

Jump - Advisor AI

WebsiteLinkedInAll Job Openings

Artificial Intelligence • Finance • SaaS

Jump - Advisor AI is a cutting-edge solution designed specifically for wealth advisors to streamline their workflow. It transforms traditional note-taking into an efficient process by converting conversations into actionable tasks, notes, and compliance records securely using AI technology. With deep integrations into popular advisor tools like Salesforce and Wealthbox, Jump allows advisors to significantly reduce administrative work and focus more on client relationships, offering features such as customizable meeting notes, automated follow-up emails, and smart task management, thereby enhancing overall service quality and compliance.

51 - 200 employees

Founded 2023

🤖 Artificial Intelligence

💸 Finance

☁️ SaaS

📋 Description

• To help with this, we’re looking for a research intern with training in observational causal inference and causal machine learning who’s excited to apply their skills to real-world problems in financial advising. • Apply observational causal inference methods with clear identification strategies to isolate conversational variables that causally influence outcomes. • Engineer structured features from unstructured transcript data (e.g., advisor talk ratio, sentiment, interruptions, trust markers, hesitations) using LLMs, embeddings, and NLP. • Analyze large-scale anonymized transcript datasets. • Strengthen the methodological rigor of our research design and analysis. • Contribute to research that pushes the financial advising industry forward. • Develop a sustainable process and reusable causal model that the team can operate independently after the internship, ensuring continuity and scalability of insights.

🎯 Requirements

• Graduate student (MA/PhD) or college senior in statistics. • Training in observational causal inference and causal machine learning. • Strong foundation in statistical modeling and data analysis. • Curiosity and exploratory creativity: the ability to go beyond validating predefined hypotheses and propose / uncover novel conversational levers. • Experience working with large datasets (Python, R, or similar). • Familiarity with NLP or interest in applying LLMs to real-world research problems. • Intellectual curiosity and a passion for using data to drive impact. • Commitment to methodological rigor and careful research design. • Bonus: Familiarity with behavioral science, financial services and causal ML libraries such as EconML, DoWhy, or CausalNex.

🏖️ Benefits

• $40/hour for part-time work (5–15 hours per week) • Flexible, remote-friendly work environment. • Hands-on research experience with a unique dataset and cutting-edge methods. • Opportunity to publish, share, and apply your work in an industry with real-world stakes.