Revenue Operations

Senior Data Scientist

The Senior Data Scientist optimizes marketplace efficiency by delivering customer analytics efforts to explain and help Workiva better understand how users engage with our products. This individual provides information to improve our products by analyzing consumer insights through data analysis and complex designs algorithm.  The Senior Data Scientist is responsible for ensuring that all Workiva products are hitting pace and generating maximum revenue per impression. The Senior Data Scientist predicts sales and marketing efforts that will provide highest returns.

Responsibilities:
  • Data Analysis: Uses big data to understand and communicate how customers interact with Workiva products and to predict what customers will want in the future
  • Conducts advanced data analysis and complex designs algorithm
  • Works iteratively with clients to design experiments, test hypotheses, build models and validate findings
  • Recommends ongoing improvements to methods and algorithms that lead to findings, including new information
  • Presents and depicts the rationale of findings in easy to understand terms for the business
  • Collaborates with others in the pursuit of common missions, vision, values and mutual goals
  • Stakeholder Relationship Management: Collaborates with Information Technology teams and business stakeholders to identify new opportunities for software innovation
  • Acts as the primary interface to stakeholders to gain a comprehensive understanding of business vision, requirements and feature needs
  • Creates, maintains, prioritizes, and sequences the product backlog based on business value or ROI from which the team will execute
  • Conveys the business vision and goals associated with the product to the project team in order to ensure that delivery is focused on business value
  • Collaborates with business stakeholders as well as the project team to create and maintain release roadmaps based on projected team velocity, estimated size of features, and business priority
Skills:
  • Excellent verbal, written, and interpersonal communication skills
  • Ability to deal with very granular data
  • Capable of using analytics to drive key success metrics related to yield management and revenue generation
  • Works with others to develop, refine, and scale data management analytics procedures, sys
  • Self-motivated with strong propensity for action, results and continuous improvement
  • The ability to work successfully in a high-energy, fast paced, rapidly changing environment is necessary
  • Exceptional organizational skills with the ability to multi-task and manage multiple processes, programs, and procedures simultaneously while working under pressure to meet deadlines
  • Ability to work autonomously
  • Ability to create examples, prototypes, demonstrations to help management better understand the work
Experience:
  • 4+ years post university experience in advanced analytics in the fields of data science and applying specific data analytics methods
  • Expert knowledge in conducting statistical analytics (statistical modeling, clustering, predictive analysis)
  • Experience in Machines learning, Algorithms, Python, Java, C++, and one or more business intelligence and data discovery systems:  Qlikview, Tableau, Alteryx
  • Experience in database technologies: SQL, SQLServer and NoSQL databases
Education:
  • Bachelor's Degree in Computer Science, Mathematics, Statistics, Engineering, or a related field
Working Conditions & Physical Requirements:
  • Depending on assigned work location, walking outdoors between company campus facilities in a variety of weather conditions may be necessary to perform responsibilities of this position
  • Less than 10% travel is required to meet with employees, vendors and/or suppliers
Individuals seeking employment are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, status as a protected veteran, or disability.
Team 
Revenue Operations
Job Type 
Full-Time
Locations 
Denver, Colorado
Chicago, Illinois
Ames, Iowa
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