Location:Lincoln, NE

As a key contributor to company's Information Technology department, the Senior Data Science Manager role is defined as follows:

• Develop the analytics to best drive insights across the company business lines.Demonstrated ability to play a leadership role in large, complex analytical projects.
• Develop compelling narratives that connect modeling results with client business problems.
• Provide insights to senior management to support strategic decision-making, preparing and delivering insights and recommendations based on analysis.
• Lead and create a team of data scientists
• Provide POVs and thought leadership on modeling topics
• Provide technical leadership across multiple teams, by understanding a key technology space deeply enough to help guide strategyInspire data science innovations that fuel the growth of company as a whole

• Provides leadership in advanced engineering, data science and analytics in the development of current or future products, technologies or services.
• Lead a team of data scientists to design, prototype, implement and test predictive and prescriptive analytic modelsPartner with Data Engineers and Project Managers to deliver end-to-end solutions
• Partner with cross-functional teams to identify and explore opportunities for the application of machine learning.
• Applies artificial intelligence and machine learning techniques to solve complex questions or fuel new business opportunitiesBuild and/or utilize toolsets and set up processes for extracting information from unstructured data streams.
• Implements data and analytics solutions, through data science techniques, that solve business problems and create business value.
• Provides technical guidance and mentoring to business insight and visualization teams, as needed.
• Leads and executes independent quantitative research projects, leveraging data from multiple sources
• Uses best practices to understand the data and develop statistical, analytical techniques to build models that address business needs.

• MS or PHD degree preferred in statistics, applied mathematics, or computer science (machine learning)
• 5+ years with predictive modeling techniques and experience in leading predictive modeling initiatives
• 3+ years of management experience
• Ability to break down complex business and technical problems into opportunities for analytical study
• Extensive knowledge and experience in data science, including expertise in one or more of: machine learning, big data/data mining, statistics, business/customer intelligence, data modeling, databases, data warehousing, or a similar field.
• Business application of the following techniques hierarchical Bayesian, Markov chain Monte Carlo, random forests, generalized boosted models, generalized additive models, neural networks, time-series forecasting, game theory, conditional probabilities or other similar approaches
• Deep knowledge of statistical areas such as ANOVA, multiple regression, timeseries modeling, principal component analyses, decision trees, clustering, etc.
• Experience programming in R, SQL, PythonAutomate data wrangling, iterative solution search and operationalization of models, working alongside data architects.
• The ability to handle missing data through an algorithmic approach such as multiple imputations to enable insights in sparse and messy datasets
• Significant experience coding and maintaining predictive algorithmsSuperior research, statistical, analytical, processing and mathematical skills with ability to structure and conduct analyses
• Fluency with analytics platforms like SAS, DSX or SPSS, Data Robot, Alteryx, etc.
• Exceptional troubleshooting skills and thriving in high-expectation scenario with many stakeholders.

• The skill of presenting complicated data in a way that allows the audience to focus on the underlying trends and insightsExplain complex modeling approaches in layman\'s terms and discuss modeling results and business case impact with non-technical business users.
• Ability to extract insights to identify growth opportunities and effectively communicate outcomes and recommendationsEnthusiasm for learning the practical application of statistical analysis to address business issues.
• Strong sense of ownership, relentless curiosity, and self-driven approach to problem solving.
• Established professional communication, presentation, and influencing skills
• Strong organizational and project management skills, to ensure you can keep on top of your own and others workloadLead effective data analysis that may suggest risk or opportunities for client.
• Partnership/collaboration with marketing business partners and other enterprise teams.