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Data Scientist
Data Scientist
The Data Scientist will design and deploy advanced analytics and machine learning solutions to address investment and operational challenges at Cortland. This role involves partnering with stakeholders, building and maintaining models, and collaborating with engineering teams to deliver production-ready insights that drive growth.
About the role
Role Overview
As a Data Scientist, you’ll design and deploy advanced analytics and machine learning solutions that address critical investment and operational challenges. Your work will transform complex data into scalable, production‑ready insights that drive smarter decisions and accelerate Cortland’s growth.
- Partner with business stakeholders to identify, prioritize, and deliver high‑value predictive and optimization use cases.
- Design, build, and maintain machine learning and statistical models that support ongoing operational and investment strategies.
- Collaborate with data and engineering teams to establish the infrastructure, pipelines, and processes required for production analytics.
- Develop end‑to‑end solutions, including model development, deployment, monitoring, and continuous improvement.
- Leverage BI, GIS, and visualization tools to clearly communicate insights to technical and non‑technical audiences.
- Lead enablement and education efforts to help teams effectively adopt and operationalize predictive analytics.
- Stay current on emerging data science tools, platforms, and methodologies, bringing relevant innovations into the organization.
Qualifications
- Bachelor’s degree in a STEM‑related field (e.g., statistics, applied math, computer science, engineering, business analytics) required; Advanced degree preferred.
- 2+ years of professional experience applying data science or advanced analytics in a business environment.
- Strong foundation in statistical modeling, machine learning, clustering, classification, recommendation systems, and optimization techniques.
- Proficiency in Python and SQL; experience with Spark, Scala, or similar tools is a plus.
- Working knowledge of cloud platforms and data ecosystems (AWS or Azure), including tools such as Databricks, EMR, RDS, and S3.
- Experience working with large, complex datasets and resolving performance or memory constraints.
- Solid business intuition with the ability to explain analytical approaches, tradeoffs, and outcomes clearly.
- Excellent communication skills, with the ability to present insights visually and tell a compelling data‑driven story.