Application Guide
How to Apply for Senior Applied Machine Learning Scientist
at Workiva
🏢 About Workiva
Workiva is pioneering integrated ESG reporting, combining data transparency with climate impact compliance. This mission-driven focus on sustainability and regulatory technology sets it apart, offering the chance to work on impactful AI solutions in a growing field.
About This Role
As a Senior Applied ML Scientist, you'll own end-to-end AI/ML projects from conception to deployment, directly influencing ESG reporting products. Your work will involve building scalable ML infrastructure and mentoring teams, driving both technical excellence and business outcomes.
💡 A Day in the Life
Your day might start with a stand-up to review ML pipeline performance, then dive into designing a new feature for ESG data classification. After lunch, you could mentor a junior scientist on model deployment, and end the day collaborating with product teams to align on priorities for the next quarter.
🚀 Application Tools
🎯 Who Workiva Is Looking For
- Proven experience (2+ years) delivering production ML solutions, ideally in a cloud environment (AWS, Azure, GCP).
- Strong Python skills and familiarity with MLOps tools (e.g., MLflow, Kubeflow, Docker) for scalable pipelines.
- Ability to lead technical initiatives and mentor junior scientists, with a track record of cross-functional collaboration.
- Interest or experience in ESG, sustainability, or regulatory domains is a plus, but not required.
📝 Tips for Applying to Workiva
Highlight specific ML projects you've owned end-to-end, emphasizing business impact and scalability.
Showcase your MLOps experience: mention tools, cloud platforms, and how you ensured model reliability and monitoring.
Tailor your resume to include leadership examples: leading technical initiatives or mentoring peers.
If you have any ESG or sustainability-related projects, even personal, mention them to show domain alignment.
Use the cover letter to connect your passion for climate impact with Workiva's mission, not just generic AI enthusiasm.
✉️ What to Emphasize in Your Cover Letter
['Emphasize your experience in building and deploying ML solutions at scale, with concrete examples.', "Discuss your leadership style and how you've mentored others or driven technical direction.", "Express genuine interest in ESG reporting and how your skills can further Workiva's mission.", 'Mention your familiarity with MLOps best practices and cloud infrastructure, tying them to reliability and scalability.']
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Read Workiva's ESG reporting platform details and understand their data integration challenges.
- → Look into recent regulatory trends in ESG (e.g., SEC climate disclosure rules) to grasp the domain's importance.
- → Explore Workiva's engineering blog or tech talks to understand their ML stack and culture.
- → Check their LinkedIn for recent projects or partnerships related to AI and sustainability.
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Focusing only on model accuracy without discussing deployment, monitoring, or business impact.
- Omitting MLOps experience or cloud platform specifics, which are key requirements.
- Submitting a generic application without showing understanding of Workiva's ESG mission.
📅 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:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!