Data Science Senior Analyst (Data Scientist)

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Job Title:
Data Science Senior Analyst (Data Scientist)

Department:
Advancement Business Intelligence

The Ohio State University’s Office of Advancement seeks a naturally curious, creative thinker to collaborate as a Data Science Senior Analyst for Audience Insights and Strategy.  The Office of Advancement is made up of professionals in the areas of alumni engagement, fundraising, business planning and operations who work to build a community of lifelong champions who support and advocate for Ohio State.

The Senior Analyst leads the development, testing, and implementation of statistically sound customer models and other deep-dive analytical projects to acquire, engage and retain customers for Ohio State’s Office of Advancement. With customer data as a foundation, the Senior Analyst works with a wide range of business partners and functional teams to deliver dynamic, personalized customer experiences across all engagement channels using machine learning and artificial intelligence. The role synthesizes business data into powerful models and insights to drive decisions which propel the business forward. The Senior Analyst is expected to independently lead projects, identify data sources and their location, operationalize their finding and models, translate work products into meaningful guidance, and influence business partners.

This position provides mathematical and statistical expertise while mining, interpreting, and cleaning data. The Senior Analyst asks questions, connects the dots and uncovers opportunities that lie hidden within data – all with the ultimate goal of providing strategic decision support to business partners and creating business impact. The position translates ambiguous business problems into a conceptual analytical and technical architecture. The successful candidate will be adept at communicating and translating highly technical material to business partners in a clear, concise and patient manner. They will possess the savvy to bridge the gap between data science and business management as well as bridge the concepts, ideas and take-aways from one project to another.

The role reports to the Associate Director, Data Science and operates with a high degree of independence to make decisions, solve problems, negotiate, and adapt to shifting priorities. Expectations include exceptional communications and interactions with diverse personalities, genuine collaboration with colleagues across Advancement, the university and Wexner Medical Center, diplomacy, attention to detail and discretion and with the demonstrated ability to actively listen and advance the strategic nature and quality of discussions. It also offers a flexible schedule including remote work as agreed upon with the Associate Director, Data Science.

 
All members of Advancement are part of creating an inclusive culture that inspires and 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

80% – Advanced Analytics and Predictive Modeling

• Apply various ML and advanced analytics techniques to perform diverse classification or prediction tasks.

• Integrate domain knowledge into the ML solution (i.e., from an understanding of financial risk, customer journey, quality prediction, sales, marketing).

• Apply statistical analysis and visualization techniques to various data, such as hierarchical clustering, T-distributed Stochastic Neighbor Embedding (t-SNE), principal components analysis (PCA), etc.

• Test ML models, such as cross-validation, A/B testing, bias and fairness, stress-testing and continuously monitor execution and health of production ML models.

• Perform quality control and peer review to ensure that outputs meet quality standards and project requirements.

• Collaborate with ML operations (MLOps), data engineers, and IT to evaluate and implement ML deployment options.

• Create, package, and communicate analytic work (synthesis) using the appropriate medium for relevant insights, including impactful storylines, applicable data visualizations, key messages and recommendations to business partners.

• Work with business partners to create training and documentation to best optimize their experiences and encourage adoption of solutions.

• Establish best practices for ML development and production infrastructure (e.g., cloud, Spark, GPUs, containers).

• Design and create data pipelines for more efficient and repeatable data science projects.

• Guide and inspire the organization about the business potential and strategy of artificial intelligence (AI)/data science.

• Collaborate across the business to understand IT and business constraints.

• Prioritize, scope and manage data science projects and the corresponding key performance indicators (KPIs) for success.

• Create and deploy prototypes to demonstrate solutions and prove concepts, such as rapid prototypes/wireframes of applications, systems, and visualizations.

• Effectively communicate with project team members and sponsors throughout the project lifecycle (status updates, gaps/risks, roadblocks, testing outcomes, etc.).

• Generate and test hypotheses about the underlying mechanics of the business process using various quantitative methods.

• Network with domain experts to better understand the business mechanics that generated the data.

20% – Data Strategy

• Work with the Associate Director to create and implement the data strategy, department standards and best practices, and propose effective data architecture and technology infrastructure to support the work of the data science department.

• Create internal documentation for commonly used data tables and files.

• Work with department leadership to identify opportunities for external data acquisition and infrastructure expansion.

• Identify and communicate existing gaps or issues in our data.

• Discover new data sources, document them and promote reuse.

• Create systems, scripts, tools, and workbenches for repeatable, reusable, and reproducible analyses.

• Leverage comprehensive knowledge and experience with building and navigating multiple data sources, leveraging information for data integration, mapping, and analytics.

• Develop documentation and training materials to continually educate and promote existing data products and data usage among Advancement and university staff.

• Consult with business partners to understand, align, and deliver analytic work to support business objectives and priorities.

• Create, build and keep up to-date with the knowledge of literature, practices, and techniques in data science, business intelligence, and management communities, as well as continually growing knowledge and understanding related to Advancement business areas.

• Understand Advancement and university information systems and be a subject matter expert on our data and its usage.

Required Qualifications

• Bachelor’s degree or equivalent experience.

• Four (4) years of relevant experience.

• Experience creating models or applying machine learning.

• Knowledge of and experience with using various statistical and data mining techniques, preferably leveraged in a business or marketing setting. Examples include: generalized linear model (GLM)/regression, random forest, boosting, trees, natural language processing, clustering, neural networks, graph analysis, etc.

Desired Qualifications (We are dedicated to building a diverse and inclusive workplace and encourage you to apply even if your experience does not align perfectly )

• Bachelor’s degree in Data Science, Data Analytics, Statistics, Applied Math, Computer Science, Computer Information Systems or Management Information Systems, Marketing, Psychology or related field; or an equivalent combination of education and experience.

• Master’s degree in Statistics, Business, Computer Science, Data Science, Economics, Engineering, Mathematics or other quantitative disciplines.

• Experience in the non-profit fundraising space.

• Experience with analytics-related languages, R or Python preferred.

• Experience using SQL to create and/or pull datasets.

• Experience visualizing and presenting data for stakeholders using advanced data visualization tools like Tableau, Microsoft PowerBI, R, Python, Shiny, etc.

• Experience with cloud computing (e.g. AWS, Snowflake, Databricks, etc.) preferably with Databricks. 

• Experience with distributed computing for big data, such as with Apache Spark / Databricks.

• Demonstrable expertise in digital analytics, including Google Analytics, Google Tag Manager, Twitter analytics, and/or Facebook Insights, and using digital data in data science project work. Experience with Google Data Studio and Google BigQuery.

• Experience with clustering algorithms, journey mapping, marketing attribution, or applying data science to marketing or sales problems.

• Experience migrating statistical models into production environments and/or integrating advanced analytics into production processes.

• Experience measuring or monitoring model performance for drift and business impact.

• Experience with experimental test design.

The Office of Advancement is committed to providing tools and resources for you to learn our business, proprietary databases, university-specific processes, and advancement practices.

Commitment to Inclusion

The Office of Advancement is committed to active allyship in addressing and dismantling the inequities created by systemic racism and implicit, long-held bias. We pledge to act with kindness, respect, and integrity at all times; trust ourselves and our colleagues and empower their whole identities; and hear and see our colleagues’ ideas, voices, and perspectives, acknowledging that we are better together.

You Need to Know

Aside from the unparalleled benefits of working for The Ohio State University and working in the diverse, smart, enjoyable, and growing city of Columbus, Ohio, this opportunity will provide exceptional rewards that arise from working for an institution doing worldwide life-changing teaching and research. Learn more here:  https://hr.osu.edu/careers/ .

In accordance with the Disaster Preparedness and University State of Emergency Policy 6.17 this position has been designated as a standby position.

Additional Information:

Target Hiring Range: $85,000 – $114,000

Ohio State is focused on enhancing the health and safety of our community. Therefore, the university is requiring every student, faculty and staff member to be compliant with Ohio State’s COVID-19 vaccine requirement . By the start of employment, all newly hired employees must receive at least the first dose of a two-dose series or a single dose of a one-dose series COVID-19 vaccination. Individuals who choose a two-dose series vaccination must receive the second dose within 45 days of their start date. Proof of vaccination will be required at time of hire. Candidates may request a medical or religious exemption from the vaccination requirement. Campus employees may also request an exemption for personal reasons. Ohio State Wexner Medical Center, College of Medicine or OSUP Employees are not eligible for personal exemptions. All exemptions are subject to Ohio State’s approval and subject to change, including revocation, due to legal and regulatory requirements.

Location:
University Square North (1031)

Position Type:
Regular

Scheduled Hours:
40

Shift:
First Shift

Final candidates are subject to successful completion of a background check.  A drug screen or physical may be required during the post offer process.

Thank you for your interest in positions at The Ohio State University and Wexner Medical Center. Once you have applied, the most updated information on the status of your application can be found by visiting the Candidate Home section of this site. Please view your submitted applications by logging in and reviewing your status. For answers to additional questions please review the frequently asked questions .

The Ohio State University is an equal opportunity employer.

All qualified applicants will receive consideration for employment without regard to age, ancestry, color, disability, ethnicity, gender identity or expression, genetic information, HIV/AIDS status, military status, national origin, race, religion, sex, gender, sexual orientation, pregnancy, protected veteran status, or any other basis under the law.

Applicants are encouraged to complete and submit the Equal Employment Identification form.