Job Information
Robert Half Data Scientist: III in Columbus, Ohio
Description
Overview
We are seeking a highly analytical Data Scientist / Advanced Analytics Specialist to leverage advanced analytics, machine learning, and statistical modeling techniques to extract insights from complex business data. This role focuses on building data‑driven models, conducting large‑scale experimentation, and influencing business decisions through actionable insights.
The ideal candidate is intellectually curious, thrives in ambiguous problem spaces, and enjoys applying cutting‑edge analytics techniques to real‑world business challenges.
Key Responsibilities
Apply advanced analytics methods to extract value from structured and unstructured business data
Design and execute large‑scale experiments and develop data‑driven models to answer complex business questions
Conduct research on emerging techniques and tools in machine learning, deep learning, and artificial intelligence
Define requirements used to train, evaluate, and evolve predictive and deep learning models
Analyze results and present data‑based recommendations to product, business, and technical teams
Influence decision‑making through clear, compelling data storytelling and insights
Support ongoing analytics initiatives and perform additional duties as assigned
Requirements
Required Qualifications
Master’s degree completed by Spring 2025 in:
Computer Science
Information Systems
Decision Sciences
Statistics
Operations Research
Applied Mathematics
Engineering
Or a related STEM discipline
OR
Bachelor’s degree with 3+ years of professional experience in analytics or data science
Hands‑on experience with:
R / RStudio
Python
SAS
SQL / NoSQL
Strong analytical, quantitative, and problem‑solving skills
Preferred Qualifications
Up‑to‑date knowledge of machine learning and advanced analytics tools and techniques
Experience with predictive modeling methodologies
Ability to work with both structured and unstructured data sources
Experience conducting statistical analysis using advanced software, scripting languages, and packages
Exposure to big data tools, scalable data pipelines, and web scraping techniques
Foundational experience building and deploying predictive models
Strong understanding of statistical methods including:
Bayesian networks and inference
Linear and non‑linear regression
Hierarchical and mixed‑effects models
Experience with cloud‑based machine learning platforms (e.g., AWS SageMaker)
Familiarity with machine learning frameworks such as TensorFlow, scikit‑learn, or caret
Background in financial services or banking is a plus
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