Cortland

Data Scientist - Atlanta, GA

Cortland$95K — $115K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in STEM (e.g., statistics, applied math, computer science) required; advanced degree preferred.
  • 2+ years of experience in data science or advanced analytics in a business context.
  • Strong skills in statistical modeling, machine learning, and optimization techniques.
  • Proficient in Python and SQL; familiarity with Spark or Scala is a bonus.
  • Working knowledge of cloud platforms (AWS or Azure) and data tools like Databricks and EMR.
  • Experience with large datasets, focusing on performance and memory management.
  • Ability to clearly articulate analytical methods and business impacts.

Responsibilities

  • Partner with stakeholders to identify and prioritize predictive use cases.
  • Design and maintain machine learning and statistical models for strategies.
  • Collaborate with engineering teams on analytics infrastructure and processes.
  • Develop comprehensive solutions from model creation to deployment and monitoring.
  • Use BI and GIS tools to communicate insights to diverse audiences.
  • Lead AI initiatives and educate teams for effective adoption.
  • Stay updated on data science innovations and integrate them into the organization.

Benefits

  • Opportunity to design and deploy advanced analytics solutions.
  • Collaboration with business and technical stakeholders.
  • Engagement in high-impact, strategic projects.
  • Exposure to cutting-edge data science tools and methodologies.
Full Job Description
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.
  • Serve as the technical lead for AI/agentic initiatives while educating the broader teams to effectively adopt.
  • 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


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