Senior Analytics Engineer/ Data Scientist

Laurel

. Turn product and business data into clear, trustworthy insights leaders can act on .

Posted 10/27/2026full-timeUnited StatesSenior💰 $205,000 - $249,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in SQL and Python for data analysis and visualization, with a strong focus on building and maintaining data pipelines and analytics solutions. Proficient in leveraging BI tools and cloud platforms to deliver actionable insights and improve data quality.

Highest-signal resume keywords

Advanced SQLPython ProgrammingData Orchestration ToolsBusiness Intelligence ToolsCloud Platform Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonData ModelingETL PipelinesMachine LearningData WarehousingData VisualizationAnalytics Lifecycle ManagementPerformance TestingROI Analysis

Soft Skills

Problem-SolvingCommunicationTime Management

Tools & Technologies

AirflowThoughtSpotSnowflakeBigQueryRedshiftAWSGCPAzureDbtKubernetes

Industry Keywords

Data ScienceBusiness Impact ReportsCustomer-Facing PresentationsCI/CD PipelinesDevOps Practices

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSAzureBigQueryCloudD3.jsETLGoogle Cloud PlatformJavaScriptKubernetesPandasPythonSnowflakeSQLTableauTerraform

About the role

Key responsibilities & impact

Turn product and business data into clear, trustworthy insights leaders can act on
Own the analytics lifecycle from ingestion and modeling to BI visualization and decision enablement
Deliver self-serve insights using SQL/Python and embedded BI such as ThoughtSpot
Run recurring ROI analyses and Business Impact Reports
Write performant SQL and pandas and productionize repeatable jobs with scheduling, alerts, and anomaly checks using orchestration tools such as Airflow
Own metric definitions and create reusable SQL data models as the analytics source of truth
Quantify and communicate Laurel's impact with the CX team
Prepare executive-ready materials and join customer-facing presentations
Deliver customer-facing ThoughtSpot dashboards and concise actionable insights
Add validation tests and monitoring, triage data issues, and collaborate with Product/Engineering to improve data quality
Design, build, and maintain Laurel's Analytics Data Warehouse
Create scalable ETL pipelines from PMS, Web Analytics, and WebApp sources
Deploy and maintain business intelligence tools
Prototype, build, and test ML models to validate hypotheses and generate insights for product features

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
3+ years of professional experience as a Data Scientist
Advanced SQL and Python
Experience with data orchestration tools such as Airflow, Prefect, or Dagster
Proficiency in modern data warehouses such as Snowflake, BigQuery, or Redshift
Familiarity with data modeling, warehousing principles, and BI tools such as ThoughtSpot, PowerBI, or Tableau
Cloud platform expertise in AWS, GCP, or Azure
Knowledge of dbt, Kubernetes, and Terraform
Exposure to CI/CD pipelines and DevOps practices
Strong problem-solving and communication skills
Ability to work in a fast-paced startup environment and manage multiple priorities
Ability to work hybrid from the San Francisco office 3 days per week
Must be legally authorized to work in the United States
Laurel is unable to provide visa sponsorship
Nice to have: experience with knowledge worker productivity tools, modern data visualization libraries such as D3.js, and ML/AI model prototyping

Benefits

Comp & perks

Generous equity
Comprehensive medical/dental/vision coverage with covered premiums
401(k)
Wellness stipend
Commuter stipend
FSA stipend
Bi-annual, in-person company off-sites
Paid time off
Retirement planning options
Health and wellness programs