Application Guide

How to Apply for Staff Decision Scientist

at Workiva

🏢 About Workiva

Workiva is pioneering the integration of ESG reporting with financial data, making it a leader in transparent climate impact and compliance. Its remote-first culture and focus on data-driven sustainability offer a unique opportunity to work on high-impact projects that shape corporate responsibility. The company's commitment to innovation and employee growth makes it an attractive place for data scientists who want to drive meaningful change.

About This Role

As a Staff Decision Scientist, you will lead causal analyses to uncover key drivers of business outcomes, directly influencing senior leadership decisions. You will own data products that enable self-service analytics across the company, translating strategic goals into measurable metrics. This role is critical for building a data-driven culture and mentoring the next generation of analysts.

💡 A Day in the Life

A typical day might start with a stand-up with your team to discuss progress on causal analyses and data product development. You'll spend time in Snowflake running complex queries, then meet with product managers to refine metrics for a new ESG feature. Later, you might mentor a junior analyst on their A/B test design and present findings to senior leadership on customer churn drivers.

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🎯 Who Workiva Is Looking For

  • Experienced in leading hypothesis-driven causal inference projects (e.g., A/B testing, quasi-experimental designs) in a tech company, with a track record of influencing product or business strategy.
  • Expert in SQL and Snowflake, with hands-on experience using Cortex for advanced analytics; comfortable with AI-assisted tools to accelerate workflows.
  • Strong communicator who can translate ambiguous business questions into structured analytical plans and present findings to senior leadership.
  • Passionate about mentoring junior analysts and fostering a collaborative data culture, with a growth mindset and willingness to share knowledge.

📝 Tips for Applying to Workiva

1

Tailor your resume to highlight specific causal inference projects (e.g., uplift modeling, instrumental variables) and quantify their business impact (e.g., revenue lift, cost savings).

2

Mention your experience with Snowflake Cortex explicitly, including any use of its machine learning or AI features, as this is a key requirement.

3

Showcase your ability to build self-service data products (e.g., dashboards, metric stores) that enabled non-technical stakeholders to make data-driven decisions.

4

Include examples of mentoring or leading data culture initiatives, such as running internal workshops or creating documentation standards.

5

In your cover letter, connect your work to Workiva's mission of ESG transparency—explain how your analytics skills can help clients measure and improve sustainability metrics.

✉️ What to Emphasize in Your Cover Letter

["Emphasize your experience with causal inference and how it drove actionable insights for business strategy, aligning with Workiva's need for rigorous decision science.", 'Highlight your proficiency with Snowflake and AI tools, demonstrating your ability to leverage modern data infrastructure for scalable analytics.', 'Show your passion for mentoring and building data culture, which is crucial for this senior role.', "Connect your personal values to Workiva's mission of simplifying ESG reporting; explain why you're excited to contribute to sustainability through data."]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Explore Workiva's ESG reporting platform: understand how they integrate financial and non-financial data for clients like Unilever or Google.
  • → Read recent blog posts or case studies on Workiva's website about their approach to data-driven sustainability and climate risk.
  • → Check out Workiva's engineering blog or data science publications to understand their tech stack (e.g., Snowflake, Sigma) and data culture.
  • → Review the company's latest earnings calls or press releases to see how they discuss data and analytics as a competitive advantage.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Walk me through a causal inference project you led: how did you identify the causal question, choose the method (e.g., diff-in-diff, propensity score), and validate assumptions?
2 How would you design a metric to measure the impact of a new ESG feature on customer retention?
3 Explain a time you turned an ambiguous business question (e.g., 'Why are customers churning?') into a structured analysis plan with clear deliverables.
4 How do you mentor junior analysts? Give an example of a technique you used to help them improve their analytical rigor.
5 Describe your experience with Snowflake Cortex: what features have you used (e.g., Cortex Search, Cortex Analyst) and how did they improve your workflow?
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⚠️ Common Mistakes to Avoid

  • Don't focus solely on machine learning models (e.g., deep learning) without emphasizing causal inference and hypothesis testing, which are core to this role.
  • Avoid generic statements about being 'data-driven'—instead, provide specific examples of how you've influenced decisions with rigorous analysis.
  • Don't neglect to mention your experience with Snowflake or similar cloud data warehouses; missing this could signal a lack of fit for the required tech stack.

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Workiva!

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