Lead Data Scientist

Remote from: USA
Salary, yearly, USD: 170,000 - 215,000
Department: Data Science & Analytics
Employment type: Full Time,
Job posted: 17 Jul 2026
Apply before: 17 Aug 2026
Experience level: Senior
Views / Applies: 34 / 4

Powering the future of trust by amplifying the advisory and audit engagement experience for CPA firms and their clients.

Computer Software
2019

Actively Hiring

AI Summary

Fieldguide is a remote-first startup building software to automate audit and advisory workflows. They seek a Lead Data Scientist to join their Data Science team and build customer-facing analytics features. The role involves analyzing large datasets, creating dashboards, and improving data infrastructure. You will work closely with Product, Design, Engineering, and Customer teams to drive data-driven decisions. This position offers the opportunity to shape intelligent workflows for audit firms using proprietary datasets.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight This role requires 5+ years of experience and tackling complex, ambiguous problems in a startup environment, indicating a high level of difficulty.

Salary Analysis

AI Insight The offered salary range of $170,000-$215,000 is competitive with the US market median for Lead Data Scientists. It falls within the typical market range of $150,000-$250,000, reflecting the seniority and impact of the role.

Core Skills Required

Data Science SQL Python ETL Pipelines dbt Airflow Data Visualization Machine Learning Analytics Data Modeling

Cover Letter Sample

Dear Hiring Team,

I am excited to apply for the Lead Data Scientist position at Fieldguide. With over 5 years of experience in data science and a strong background in building scalable data infrastructure and customer-facing analytics, I am confident in my ability to drive actionable insights for your platform. My expertise in SQL, Python, and tools like dbt and Airflow aligns perfectly with the requirements of this role.

I have a proven track record of leading data initiatives that uncover operational inefficiencies and enable data-driven decision making. I thrive in collaborative environments and am passionate about leveraging data to solve complex problems. I am particularly drawn to Fieldguide's mission of automating audit workflows and would be thrilled to contribute to the development of Fieldguide Insights.

Thank you for considering my application. I look forward to the opportunity to discuss how my skills can support your team.

Sincerely, [Your Name]

Sample Interview Questions

Can you describe a time when you built a customer-facing analytics feature from scratch? What was the impact?

In my previous role, I built a real-time dashboard for our clients to monitor their campaign performance. I started by gathering requirements from stakeholders, designed the data model, and implemented ETL pipelines using Airflow and dbt. The dashboard reduced client reporting time by 40% and improved decision-making speed.

How do you approach data quality and completeness in large datasets?

I implement automated validation checks at each stage of the pipeline, using tools like Great Expectations. I also work with engineering to ensure upstream data sources are reliable. For completeness, I set up monitoring and alerting for data freshness and volume anomalies, and regularly audit the data against business logic.

Describe your experience with modern data tooling like dbt, Airflow, and orchestration frameworks.

I have extensive experience with dbt for data transformation and Airflow for orchestration. In my last project, I used dbt to build modular data models with testing and documentation, and Airflow to schedule and monitor pipelines. This setup improved data reliability and reduced manual effort.

How do you translate complex data insights into strategic recommendations for non-technical stakeholders?

I focus on storytelling with data—using clear visualizations and KPI summaries that highlight the key takeaways. I also tailor the communication to the audience, avoiding jargon and emphasizing business impact. For example, I once presented a churn analysis to product managers that led to a 15% reduction in customer churn.

Tell me about a time you led a data science project with ambiguous requirements. How did you handle it?

In a project to identify operational inefficiencies, the initial problem statement was vague. I conducted interviews with stakeholders to understand pain points, then defined clear success metrics. I built a prototype dashboard and iterated based on feedback. The final solution reduced audit time by 20% for clients.

About Us

Fieldguide is establishing a new state of trust for global commerce and capital markets by automating and streamlining the work of assurance and audit practitioners, specifically in cybersecurity, privacy, and financial audits. Put simply, we build software for the people who enable trust between businesses.

We’re based in San Francisco, CA, but built as a remote-first company that enables you to do your best work from anywhere. We’re backed by top investors, including Growth Equity at Goldman Sachs Alternatives, Bessemer Venture Partners, 8VC, Floodgate, Y Combinator, DNX Ventures, Global Founders Capital, Justin Kan, Elad Gil, and more.

We value diversity—in backgrounds and experiences. We need people from all backgrounds and walks of life to help build the future of audit and advisory. Fieldguide’s team is inclusive, driven, humble, and supportive. We are deliberate and self-reflective about the kind of team and culture we are building, seeking teammates who are not only strong in their own aptitudes, but who also care deeply about supporting each other’s growth.

As an early-stage startup employee, you’ll have the opportunity to help build the future of business trust. We make audit practitioners’ lives easier by consolidating up to 50% of their work and improving work-life balance. If you share our values and enthusiasm for building a great culture and product, you’ll find a home at Fieldguide.

About the Role

The Data Science team at Fieldguide leverages novel, proprietary datasets to build Fieldguide Insights —a product that delivers new-to-the-industry visibility into audit and advisory execution and performance. You’ll work closely with Product, Design, Engineering, and Customer teams to build analytics and data science models that uncover key performance drivers, identify operational inefficiencies, and enable customers to make informed, data-driven decisions.

This role is ideal for someone who thrives on solving complex, ambiguous problems and is excited to shape the future of intelligent workflows for audit and advisory firms.

What You’ll Do

Analyze large volumes of structured and unstructured data to uncover trends, patterns, and actionable insights
Define and track key metrics to evaluate firm, team, and engagement performance using Fieldguide’s industry-leading dataset
Design and build customer-facing analytics features and dashboards that deliver measurable value by uncovering opportunities and supporting strategic decision-making
Build and maintain scalable data infrastructure—including preprocessing, ETL pipelines, data modeling, orchestration, and monitoring—to support analytics and product insights
Lead efforts to improve data quality, completeness, and accessibility across internal systems and product experiences

Who You Are

5+ years of experience as a Data Scientist, Data Analyst, or similar role working with large, complex datasets
Strong SQL skills and proficiency in Python (e.g., pandas, NumPy)
Experience shipping production code for customer-facing products
Experience with modern data tooling such as dbt, Airflow, or equivalent orchestration and transformation tools
Hands-on experience with data visualization tools (e.g., Tableau, Power BI, Looker) to communicate insights effectively
Technical expertise in building scalable data models, ETL pipelines, and data architecture
Business acumen with the ability to translate data into strategic insights
Excellent problem-solving, collaboration, and communication skills
BA/BS in Computer Science, Engineering, Math/Statistics, Business, or a related field; a graduate degree in a quantitative field is preferred