Sr. Analytics Engineer/ Data Scientist

Posted 6 Days Ago
2 Locations
Hybrid
205K-249K Annually
Senior level
Automation
The Role
Own the analytics lifecycle: build SQL/Python analyses and ETL, define metrics and reusable data models, produce customer-facing ThoughtSpot dashboards and ROI analyses, prototype ML solutions, improve data quality, and design and maintain the analytics data warehouse and pipelines.
Summary Generated by Built In

Laurel is on a mission to return time. As the leading AI Time platform for professional services firms, we’re transforming how organizations capture, analyze, and optimize their most valuable resource: time. Our proprietary machine learning technology automates work time capture and connects time data to business outcomes, enabling firms to increase profitability, improve client delivery, and make data-driven strategic decisions. We serve many of the world's largest accounting and law firms, including EY, Aprio, Crowell & Moring, and Frost Brown Todd, and process over 1 billion work activities annually that have never been collected and aggregated before Laurel’s AI Time platform.

Our team comprises top talent in AI, product development, and engineering—innovative, humble, and forward-thinking professionals committed to redefining productivity in the knowledge economy. We're building solutions that empower workers to deliver twice the value in half the time, giving people more time to be creative and impactful. If you're passionate about transforming how people work and building a lasting company that explores the essence of time itself, we'd love to meet you.

About the Role

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.

In addition, you’ll apply machine learning to real-world product and business problems. You should be comfortable prototyping AI/ML models in notebooks, experimenting with approaches (classification, clustering, regression, NLP, etc.), and translating findings into actionable insights for the product and business.

What you will do

  1. 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).

  2. 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.

  3. 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.

  4. Ship dashboards & actionable insights

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

  5. Raise data quality & instrumentation

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

  6. Data Platform Development

    • Design, build, and maintain Laurel’s Analytics Data Warehouse as the single source of truth for analytics and reporting needs.

    • Create scalable ETL pipelines to ingest, process, and organize data from diverse sources (PMS, Web Analytics, WebApp).

    • Deploy and maintain Business Intelligence tools to provide analytics and reporting capabilities.

You will be a great fit if you have

  • Education: Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

  • Experience: 3+ years of professional experience as a Data Scientist. Ideal candidates will be comfortable working with large-scale data systems.

  • Technical Proficiency:

    • Advanced SQL and Python

    • Experience with data orchestration tools (e.g., Airflow, Prefect, Dagster).

    • Proficiency in modern data warehouses (e.g., Snowflake, BigQuery, Redshift).

    • Familiarity with data modeling, warehousing principles, and BI tools (e.g., Thoughtspot, PowerBI, Tableau).

    • Ability to build ML models and quickly prototype solutions (classification, clustering, regression, NLP) that inform product direction.

  • Experience With:

    • Cloud platform expertise (AWS, GCP, Azure).

    • Knowledge of dbt, Kubernetes, and Terraform.

    • Exposure to CI/CD pipelines and DevOps practices.

  • Soft Skills:

    • Strong problem-solving and communication skills.

    • Ability to work in a fast-paced startup environment and manage multiple priorities.

Nice to haves

  • Experience with knowledge worker productivity tools

  • Familiarity with modern data visualization libraries (e.g., D3.js)

  • ML and AI: Prototype, build and test ML models to quickly validate hypotheses and generate insights that guide Laurel product features

Flexibility and Logistics

  • Location: This role will be hybrid based in our San Francisco office, 3 days per week. We will consider exceptionally qualified candidates based in other US-locations on a case by case basis.

  • Compensation: Competitive salary, generous equity, comprehensive medical/dental/vision coverage with covered premiums, 401(k), additional benefits including wellness/commuter/FSA stipends. For candidates based in San Francisco the compensation range for this role is $205,000-$249,000 USD. Final compensation amounts will be determined based on several factors including candidate experience, qualifications and expertise and may vary from the amounts listed.

  • Visa Sponsorship: Unfortunately we are unable to provide Visa Sponsorship at this time.

Why join Laurel:
  • To date, we've secured significant funding from renowned venture capitalists (Google Ventures, IVP, Anthos, Upfront Ventures), as well as notable individuals like Marc Benioff, Gokul Rajaram, Kevin Weil, and Alexis Ohanian

  • A smart, fun, collaborative, and inclusive team

  • Great employee benefits, including equity and 401K

  • Bi-annual, in-person company off-sites, in unique locations, to grow and share time with the team

  • An opportunity to perform at your best while growing, making a meaningful impact on the company's trajectory, and embodying our core values: understanding your "why," dancing in the rain, being your whole self, and sanctifying time

We encourage diverse perspectives and rigorous thinkers who aren't afraid to challenge the status quo. Laurel is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. We are not able to support visa sponsorship or relocation assistance. 

If you think you'd be a good fit for this role, we encourage you to apply, even if you don’t perfectly match all the bullet points in the job description. At Laurel, we strive to create an inclusive culture that encourages people from all walks of life to bring their unique, diverse perspectives to work. Every day, we aim to build an environment that empowers us all to do the best work of our careers, and we can't wait to show you what we have to offer!

Skills Required

  • Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)
  • 3+ years professional experience as a Data Scientist or Analytics Engineer
  • Advanced SQL
  • Advanced Python (including pandas)
  • Experience with data orchestration tools (Airflow, Prefect, Dagster)
  • Proficiency with modern data warehouses (Snowflake, BigQuery, Redshift)
  • Familiarity with data modeling, warehousing principles, and BI tools (ThoughtSpot, PowerBI, Tableau)
  • Ability to prototype and build ML models (classification, clustering, regression, NLP)
  • Cloud platform experience (AWS, GCP, Azure)
  • Knowledge of dbt, Kubernetes, and Terraform
  • Exposure to CI/CD pipelines and DevOps practices
  • Strong communication and ability to present to technical and non-technical stakeholders
  • Experience with knowledge worker productivity tools
  • Familiarity with modern data visualization libraries (D3.js)
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The Company
HQ: San Francisco, CA

What We Do

Laurel is the world’s first AI Time platform for professional services firms. The company's AI transforms how organizations track, analyze, describe, and optimize their most valuable resource: time. By automating work time and connecting time data to business outcomes, Laurel enables firms to increase profitability, improve client delivery, and make data-driven strategic decisions. Founded in 2018, Laurel serves many of the world's largest accounting, consulting and law firms.

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