Principal Data Scientist
1 month ago
About the Role
We are looking for a Principal Data Scientist to support the transformation of Blackbaud’s enterprise data into a strategic asset. As a Principal Data Scientist, you’ll guide the use of internal data platform (combination of data warehouse, data lake, data pipelines, machine learning, and visualization tools) for effective data discovery, predictive modeling, and machine learning.
What you’ll do
- Prioritize data science projects within the team roadmap.
- Lead discussions with business partners to understand business problems, perform data discovery to identify key data required, and document data requirements in the Insights team backlog.
- Develop and deploy code to enhance and grow our use of predictive modelling and machine learning techniques.
- Improve data predictions through iterative testing, monitoring, and measurement.
- Contribute to the platform code base expanding on data pipelines, data models, data transformations, data quality tests, and documentation.
- Assess ML and other analytics capabilities emerging within IT systems and help develop the strategy for performing advanced analytics.
- Partner with Data Scientists in other parts of the business to identify important data assets, key metrics, and other capabilities that would be useful to incorporate into the internal platform.
- Present key findings and insights to technical and non-technical audiences at various levels of the organization.
- Evangelize the effective use of IT tools for performing data discovery, analysis, machine learning, and visualization and coach and guide analysts on best practices.
- Coach, mentor, and guide data analysts in data science methodologies to aid in their development.
What you’ll bring
- 8 or more years of experience performing quantitative analysis
- Experience with supervised machine learning algorithms, best practices and pitfalls
- Experience with data analysis in Python, R or similar
- Demonstrated experience in influencing business decisions and driving business value
- Familiarity with how software and projects are organized, issue tracking, creating and merging pull requests and agile processes.
What we’ll prefer you to have
- Experience with time series modeling, multi series modeling, NLP featurization, anomaly detection, unsupervised and semi-supervised learning methods, image recognition
- Academic publications in data analysis or machine learning techniques
- Experience with DataBricks and MLflow
- Experience with Azure OpenAI Studio
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