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Data Scientist

Job

TekLeaders, Inc

Columbus, OH (In Person)

Full-Time

Posted 4 days ago (Updated 1 day ago) • Actively hiring

Expires 7/4/2026

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Job Description

Role:
Data Scientist Location:
Columbus, OH -
Only Locals Duration:
Long Term Duties and Responsibilities:
Ability to use advanced analytics methods to extract value from business data. Ability to perform large-scale experimentation and build data-driven models to answer business questions. Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence. Determines requirements that will be used to train and evolve deep learning models and algorithms. Influences product teams through presentation of data-based recommendations. Performs other duties as assigned.
Basic Qualifications:
Master's degree completed by Spring 2025 in Computer Science or Information Systems, Decision Sciences, Statistics, Operations Research, Applied Mathematics, Engineering, or a STEM degree or in lieu of a Master's degree, Bachelor's degree with a minimum of 3 years work experience in analytics or data science Experience with
R, RStudio, Python, SAS, SQL, NoSQL Preferred Qualifications:
Up-to-date knowledge of machine learning and data analytics tools and techniques Knowledge in predictive modeling methodology Experienced at leveraging both structured and unstructured data sources Willingness and ability to learn new technologies on the job Work and/or educational experience conducting statistical analysis with advanced statistical software, scripting languages, and packages Work and/or educational experience with big data analysis tools and techniques Foundational knowledge of building and deploying predictive models, web scraping, and scalable data pipelines Understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling Experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker) Experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret)