Data Scientist at The Ohio State University
Posting DateSeptember 10, 2019
Location of Position
For 144 years, The Ohio State University's campus in Columbus has been the stage for academic achievement and a laboratory for innovation. It's where friendships are forged. It's where rivalries and revelry are born.
The university's main campus is one of America's largest and most comprehensive. As Ohio's best and one of the nation's top-20 public universities, Ohio State is further recognized by a top-rated academic medical center and a premier cancer hospital and research center. As a land-grant university, Ohio State has a physical presence throughout the state, with campuses and research centers located around Ohio.
The Ohio State University is proud to be a premier employer that provides an exceptional total rewards package including medical, dental, vision and many other “hidden” benefits. Our competitive benefits package is offered to all eligible faculty and staff in order to attract, develop and retain top performers eager to share their talent, time and success. Our benefits support your health and financial goals and include not only health insurance, but also generous state retirement, tuition assistance for our employees and their dependents, wellness initiatives, and much more. Please visit https://hr.osu.edu/benefits/ for detailed information. Be your best at The Ohio State University!
Duties and Responsibilities
The Office of Advancement’s Data Science team delivers wisdom in data by interacting with partners to translate problems into analytical solutions. The team delivers advanced solutions utilizing a variety of data sources and types to craft compelling and scalable advanced analytical and machine learning products that increase awareness, engagement, advocacy, and fundraising results for the university.
The Data Scientist works with analytic and business partners in a multi-faceted environment combining higher education, fundraising, engagement, and marketing to develop strategy and deliver actionable, data-driven insights and solutions. They conceptualize and create analytic strategies for complex issues, design flexible and reusable analytic tools and models, manage multiple projects simultaneously, operationalize their findings and models, translate work products into meaningful guidance, develop and deliver presentations and data visualizations, and communicate effectively with business partners.
This position serves as a technical contributor for advanced data analytics initiatives, creating value to leadership by compiling and analyzing business data from within Advancement and the university using our CRM, digital engagement platforms and other internal and external sources to provide a 360-degree view of our constituents. They are responsible for generating solutions to existing business challenges and studying the business to ask (and answer) questions nobody has asked before.
Reporting to the Associate Director, the Data Scientist is expected to be a strong technician who keeps abreast of current practices and trends, and is able to translate technical jargon in a professional manner when working with and presenting recommendations to a diverse group of business partners and clients. This position must exhibit agility when competing and/or shifting priorities exist. They must demonstrate a desire to create business value over all else, even when the competitor is statistical elegance. Conversely, they show continual improvement of theoretical and applied skills with evidence of a desire to continue technical learning and growth – both as a statistician and a business professional.
All members of Advancement are part of creating an inclusive culture that inspires an exceptionally diverse and talented team and are measured on their adherence to the following core competencies: leadership, continuous improvement, teamwork and collaboration, and communication/interpersonal effectiveness.
Duties and Responsibilities:
70% Advanced Analytics and Predictive Modeling – Evaluate the current operational environment and identify opportunities to leverage advanced analytics. Consult with business partners to understand, align, and deliver analytic work to support business objectives and priorities. Complete data science projects from start to finish, including data blending and wrangling, exploratory analysis, feature creation and selection, and model training and evaluation. Build and deploy prototypes to demonstrate solutions and prove concepts.
Proactively identify and test sources of new data. Utilize advanced SQL to create complex datasets. Manage, acquire, clean, and blend data from multiple sources to support analyses. Handle missing data and transform and explore data for understanding and further analyses. Build re-usable scripts to automate and create efficiencies. Leverage a wide range of data analysis, machine learning, and statistical modeling algorithms and methods to solve business problems, develop new predictive models and scoring, and provide insight and direction. Identify the right algorithms and statistical techniques for specific projects based on the business problem and any limitations. Blend techniques as needed for optimal performance.
Develop best-in-class solutions, tools, and data visualizations that answer strategic questions. Work with colleagues to operationalize models and products where possible. Create, package, and communicate analytic work using appropriate medium for relevant insights, including impactful story line and applicable data visualizations. Create training documentation. Consult with business partners and end-users on interpreting, understanding, and applying scoring and analysis to ensure all teams are as effective as possible. Easily explain concepts in a non-technical way that the audience can understand.
Build scripts, documentation, packages, and systems for repeatable, reusable and reproducible analyses. Demonstrate excellent organization skills throughout the development of analytical solutions by following team standards for documentation, code management, project organization, etc.
20% Analytical Strategy – Work with the Associate Director to develop and implement data strategy, department standards, and best practices; identify opportunities for external data acquisition; and propose effective data architecture and technology infrastructure to support analytical activities and increase operational efficiency. Ensure consistency of approach related to data extraction, analysis techniques, and key findings. Work with the Associate Director to develop internal documentation for commonly used data tables and files. Identify and communicate existing gaps or issues in the data.
Promote data-driven culture by developing documentation and training materials to continually educate and promote existing data products and data usage among Advancement and university staff. Actively contribute to the continuous learning mindset of the organization by bringing in new ideas and perspectives that stretch the thinking of the group. Serve as a technical resource and subject matter expert to others in advanced analytics, statistics, and machine learning. Build and keep up with the knowledge of literature, practices, and techniques in data science communities, as well as continually grow knowledge and understanding related to Advancement and university business areas. Understand Advancement and university information systems and be a subject matter expert on the data and its usage.
10% Other duties as assigned
- Advanced degree in Data Science, Statistics, Business, Computer Science, Economics, Engineering, Mathematics or other quantitative disciplines;
- Two+ years’ experience visualizing and presenting data for stakeholders using advanced data visualization tools like Tableau, D3 or Shiny, etc.;
- Experimental test design experience;
- Experience with natural language processing;
- Knowledge of full life cycle development for advanced analytic projects including experience using agile frameworks;
- Experience working with digital analytics data and projects;
- Experience migrating statistical models into production environments and/or integrating advanced analytics into production processes;
- Understanding of enterprise data warehouse, big data, cloud, BI & analytics, content management, and data management;
- Experience in the higher education or non-profit fundraising space.
- Bachelor’s degree in Data Science, Data Analytics, Statistics, Applied Math, Computer Science, Computer Information Systems or Management Information Systems, Marketing, or Psychology preferred;
- Five+ years of analytics or data science experience in a business environment to include at least three years’ experience building, validating, and leveraging machine learning models and at least two years’ experience analyzing and synthesizing data and presenting useable insights and recommending courses of action;
- Proficiency in modern analytics programming languages, like R and/or Python, as well as data extraction, manipulation, and programming using SQL;
- Strong foundational knowledge statistics/applied mathematics leveraged in a business or marketing setting;
- Proven success translating ambiguous business problems into a conceptual analytical and technical architecture;
- Strong skills manipulating missing / corrupt / unstructured data from multiple data sources to deliver key insights
In accordance with the Disaster Preparedness and University State of Emergency Policy 6.17 this position has been designated as an essential position.
The Ohio State University is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation or gender identity, national origin, disability status, or protected veteran status.