Staff Data Scientist

This role will report to the Director of Decision Science and is a part of the Data & Analytics organization within Business Technology (BT). BT powers Workiva’s growth, enhances the employee experience, and boosts organizational productivity with tech-driven transformation and innovative solutions. The Data & Analytics team drives data-driven decisions and innovations across Workiva.

As a Staff Data Scientist at Workiva, you will play a key role in driving data-driven innovation and strategic decision-making across the organization. Working as a senior member of our Decision Science team, you’ll solve complex business challenges, develop impactful data products, and influence high-level business initiatives. This role offers the unique opportunity to blend deep technical expertise with leadership responsibilities, enabling you to contribute significantly to our company’s growth and success.

You will take ownership of the full data science lifecycle—from data acquisition to deploying and monitoring models in production—while shaping our overall data strategy and fostering a culture of data-driven decision-making.

What You’ll Do 

Collaborate with Leadership: Partner with cross-functional leaders and product owners to understand business needs and translate them into data science initiatives that drive strategic decisions.

Design and Implement Solutions: Lead the design and implementation of data science solutions to address high-priority business challenges and deliver measurable impact.

End-to-End Data Science Ownership: Manage the complete data science lifecycle, including data acquisition, preprocessing, exploration, modeling, deployment, and ongoing performance monitoring of models in production.

Drive Actionable Insights: Translate complex data analyses into clear, actionable recommendations for business stakeholders, empowering data-driven decision-making across the organization.

Shape Data Strategy: Contribute to data strategy by collaborating with data engineering teams to define new data acquisition, instrumentation, metrics design, and platform technology choices.

Thought Leadership: Become a subject matter expert in both the technical and business domains, using data and insights to informing senior stakeholders on strategic goals related to product investment, revenue growth, and customer satisfaction/retention.

Foster Data Culture: Help cultivate a strong data-driven culture by actively contributing to the data and analytics community, mentoring junior team members, developing best practices, and improving team processes.

Innovate with AI & Machine Learning: Explore and apply cutting-edge techniques in AI, machine learning, and statistical analysis to stay ahead of industry trends and continuously innovate.

What You’ll Need

Minimum requirements

• 6+ years of experience in data science or related fields, complemented by a Bachelor’s, Master’s, or PhD in Data Science, Computer Science, Statistics, Mathematics, or a related discipline

Preferred Qualifications

• Technical and Analytical Expertise:

  • Proficiency in programming languages such as Python and R
  • Experience with machine learning tools like Sagemaker, MLFlow, Metaflow, Keras, and/or PyTorch
  • Advanced SQL skills and experience with large-scale data analysis
  • Knowledge of machine learning techniques, including regression, cross-validation, boosting, decision trees, clustering, CNNs, RNNs, transformers, and GANs
  • Expertise in statistical methods such as hypothesis testing, A/B testing, and causal inference
  • Experience deploying machine learning models in production environments
  • Familiarity with cloud platforms like AWS and Snowflake, big data tools like Spark, and data visualization tools such as Quicksight, Superset, or Python libraries (e.g., Seaborn, Matplotlib)

• Practical and Strategic Experience:

  • Experience deploying and optimizing machine learning models to meet business objectives
  • Familiarity with instrumentation and product event logging using tools like Splunk and New Relic
  • Knowledge of SaaS products and business models, with a focus on using data science to enhance user engagement and retention

• Interpersonal and Problem-Solving Skills: