Financial Advisor Coach – Practice Management Consultant
AlphaHire
Research Intern – Statistics, Financial Advisor Insights
Jump - Advisor AI
part-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $40 per hour
Job Level
Entry Level
Tech Stack
Python
About the role
- 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.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
observational causal inferencecausal machine learningstatistical modelingdata analysisNLPlarge datasetsPythonREconMLDoWhy
Soft skills
curiosityexploratory creativityintellectual curiositycommitment to methodological rigor
