Senior Analyst, Data Science

Where Ambition Meets Innovation

Build a career that matches all your initiative with an impressive dose of innovation. From cutting-edge resources and a collaborative environment to the freedom to make an impact and more, you'll find the ingredients you need at LPL Financial to shape your success while helping clients pursue their financial goals.

Job Overview:

We are seeking a curious and analytically rigorous Senior Analyst, Data Science to design and build models, analyses, and decision-support tools that drive transformation across the firm's home-office functions
- Service, Operations, Supervision, Compliance, Legal, and Risk
. This role sits on a small, high-leverage data science team within our Data Analytics & Reporting organization, chartered to deliver trusted, AI-enabled insights that drive measurable business outcomes for a Fortune 500 broker-dealer.

You'll closely collaborate with the team and key business partners to frame analytical problems, design and execute analyses, and translate results into actionable recommendations. This is a high-impact, hands-on role for someone who wants to apply classical data science methods - machine learning, statistics, anomaly detection, and causal inference - to consequential problems in a regulated environment, where the quality of a model depends as much on understanding the business and regulatory context as it does on the math.

Roles & Responsibilities:

Insight Generation & Analysis

• 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 the rigor and clarity expected in a regulated environment.
• Translate complex analytical outputs into clear narratives and visualizations for business stakeholders and senior leadership.

Machine Learning & Modeling

• Build, validate, and deploy supervised and unsupervised machine learning models supporting use cases such as risk tiering, surveillance and alert prioritization, anomaly detection, segmentation, and workload/cost-to-serve modeling.
• Evaluate model performance using appropriate metrics and clearly communicate trade-offs, assumptions, and limitations to both technical and non-technical audiences.
• Stay current on advances in applied ML and bring emerging methods to bear on relevant business problems.

Causal Inference & Experimentation

• Design and analyze A/B tests and observational studies to identify causal relationships and measure the impact of business initiatives.
• Apply quasi-experimental methods when randomized experiments are not feasible.
• Partner with business teams to build a culture of evidence-based decision-making.

Data & Collaboration

• Work closely with data engineers, product managers, business stakeholders, and subject matter experts to access, understand, and leverage data assets across the enterprise.
• Document analytical workflows, assumptions, code, and findings to ensure reproducibility, knowledge sharing, and audit readiness.
• Contribute to building a scalable data science practice by identifying opportunities to improve tools, processes, and methodologies.

What we are looking for?

We are looking for strong collaborators who deliver exceptional client experiences and thrive in fast-paced, team-oriented environments. Our ideal candidates pursue greatness
, act with integrity
, and are driven to help our clients succeed
. We value those who embrace creativity, continuous improvement, and contribute to a culture where we win together and create and share joy in our work.

We are also looking for someone whose experience already maps closely to the kind of work this team does. The most impactful data scientists will already be fluent in the business and regulatory context of a broker-dealer - who understand how the firm's front- and back-office functions interact, how operational and supervisory workflows are structured, how regulatory obligations shape the way work is done, and how home-office professionals across functions like Service, Operations, Supervision, Compliance, Legal, and Risk…