Biotechnology Innovation Organization (BIO) is looking to empower a data-driven organization by leading data initiatives, contributing to and executing its data strategy, and laying a strong foundation for data and analytics solutions that meet business objectives.
Requirements
- 8+ years of progressive experience in data science, modeling, analytics, and IT solution delivery.
- Expertise in SQL, NoSQL, and complex ETL/data integration strategies across distributed systems.
- Strong proficiency with modern data warehousing and architecture tools such as Snowflake, Databricks, and Data Fabric.
- Skilled in BI tools such as Power BI, Tableau, and Looker, with a focus on delivering meaningful data visualizations.
- Programming expertise in Python, R, or similar for data analytics, automation, and model deployment.
- Deep experience architecting solutions on cloud platforms such as AWS, Azure, and Google Cloud.
- Hands-on experience with Agile methodologies, Git-based version control, and CI/CD practices for efficient, high-quality delivery.
Responsibilities
- Design and implement scalable, reliable data solutions that support advanced research, analytics, and AI/ML experimentation across the enterprise.
- Translate complex research and business questions into robust data models that capture key relationships, hierarchies, and behaviors across diverse datasets.
- Drive the development of reusable, research-ready data assets and pipelines that streamline data acquisition, enrichment, quality and integration from structured and unstructured sources.
- Optimize end-to-end data workflows—from ingestion to insight—ensuring teams can efficiently explore, test, and iterate on data-driven hypotheses.
- Collaborate with cross-functional teams to build data models, dashboards, and reports that provide actionable insights and drive decision-making.
- Support data governance initiatives by promoting standards for data quality, privacy, and compliance.
- Continuously assess and improve data architecture for performance, scalability, and cost-efficiency.
Other
- Proven success leading mid- to large-scale data initiatives across cross-functional teams, driving business impact.
- Applied experience in predictive analytics, machine learning models, and AI-driven insights to support business decision-making.
- Understanding of data governance, privacy, compliance, and enterprise data quality standards.
- Excellent communicator, able to distill complex technical concepts for executive and non-technical audiences.
- Strong strategic execution skills with the ability to align technical solutions with organizational goals.
