As a Senior Analytics Engineer/Data Scientist at Laurel, you’ll turn product and business data into clear, trustworthy insights leaders can act on. You’ll own the analytics lifecycle—from ingestion and modeling to BI visualization and decision enablement. You’ll deliver self-serve insights using SQL/Python and embedded BI (e.g., ThoughtSpot). You will also help define the design patterns and data infrastructure to scale.

We’re especially interested in candidates who thrive in early-stage environments and pair analytical rigor with clear storytelling. You’ll partner closely with our CX team to quantify and communicate Laurel’s ROI, and you’ll join customer-facing presentations. You will be able to translate complex methods for non-technical leaders while going deep with technical stakeholders when needed.

Build analyses & automation (SQL/Python)

Run recurring ROI analyses (Business Impact Reports). Write performant SQL and pandas; productionize repeatable jobs (scheduling, alerts, anomaly checks) with orchestration (e.g., Airflow).

Define metrics & model the data

Own metric definitions (e.g., True Time vs. Released), create reusable SQL Data Models that serve as the analytics source of truth.

Partner with CX on customer ROI

Quantify and communicate Laurel’s impact, prepare exec-ready materials, and join customer-facing presentations—translating for both non-technical and technical stakeholders.

Ship dashboards & actionable insights

Deliver customer-facing ThoughtSpot dashboards and turn findings into concise actionable insights

Raise data quality & instrumentation

Add validation tests and monitoring, triage data issues quickly, and collaborate with Product/Engineering to improve data quality.

Sr. Analytics Engineer/ Data Scientist

Responsibilities

Qualification

Preferred

Benefits

Company

Laurel

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