Senior Analyst, Data Science

LPL Financial

Senior Analyst in Data Science at LPL Financial uncovering key insights for strategic decisions. Collaborating with teams to execute analyses and communicate findings effectively.

Posted 5/13/2026full-timeAustin • North Carolina, Texas • 🇺🇸 United StatesSenior💰 $85,902 - $143,170 per yearWebsite

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Design and execute end-to-end analyses that surface meaningful business insights, from data extraction and cleaning through modeling and interpretation.
Apply statistical methods—including hypothesis testing, regression, and causal inference—to answer business questions with rigor and clarity.
Translate complex analytical outputs into clear narratives and visualizations for business stakeholders and senior leadership.
Build, validate, and deploy supervised and unsupervised machine learning models to support segmentation, prediction, and optimization use cases.
Evaluate model performance using appropriate metrics and communicate trade-offs and assumptions to both technical and non-technical audiences.
Stay current on advances in applied ML and bring emerging methods to bear on relevant business problems.
Design and analyze A/B tests and observational studies to identify causal relationships and measure the impact of business initiatives.
Document analytical workflows, assumptions, code and findings to ensure reproducibility and knowledge sharing across the team.

Requirements

What you’ll need

2–4 years of experience in a data science, quantitative analysis, or applied research role in a business setting.
Proficiency in Python for data manipulation, statistical analysis, and machine learning, that goes beyond Jupyter notebooks; strives for clean, Git version-controlled code.
Solid grounding in statistics, probability, and machine learning fundamentals.
Hands-on experience with causal inference methods and experimental design.
Experience working with large-scale data in SQL & Snowflake; comfortable building and maintaining clean, reproducible data pipelines as needed to support modeling and analysis work.
Data visualization skills and ability to communicate findings clearly to non-technical stakeholders; note this role will not be focused on developing dashboards.
Bachelor’s degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field required; Master’s degree preferred.

Benefits

Comp & perks

401K matching
health benefits
employee stock options
paid time off
volunteer time off

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data extractiondata cleaningstatistical methodshypothesis testingregressioncausal inferencemachine learningA/B testingdata visualizationSQL

Soft Skills

communicationanalytical thinkingproblem-solvingcollaborationnarrative buildingknowledge sharing