Data Scientist

Overview

Remote
Depends on Experience
Full Time

Skills

Data Scientist
AI/ML
Python

Job Details

Job Title: Data Scientist

Location: Columbus,OH

Type: Fulltime

 

Job Description:

  • Analyzing complex decisions that AI cannot (yet) make, breaking them down into deterministic decision trees, and finding innovative ways to involve AI in those processes
  • Creating and maintaining ML pipelines to operationalize ML models.
  • Collaborating in cross-functional software/architecture design sessions to find the best solutions for the problems that we are facing.
  • Implement and optimize deep learning models for generative tasks.
  • Collaborate with software engineers to integrate models into production systems
  •  Should be able to comprehend data through exploration and visualization, spot discrepancies in data distribution
  •  Should be able to work on structured as well as unstructured data
  •  Should understand CI/CD processes in AI/ML deployment and used it in delivery.
  • Should be able to collaborate with data engineers to build data and model pipelines and maintain accuracy
  •  Should be able to take complete ownership of the assigned project

Required Skills:

  • You have at least 5 years of development experience.
  • Proficiency and extensive development experience with Python and basic libraries for machine learning such as scikit-learn, pandas
  • Proficiency in Python and Object oriented programming
  • Comfort working in a fast-paced environment with high standards for outputs
  • Able to work independently, self-organize, and motivate
  • Comfort working in a fast-paced environment with high standards for outputs
  • Understanding of AI/ML frameworks, LLM libraries, data structures, data modeling, and software architecture.
  • Proficiency with a deep learning framework such as TensorFlow, Keras, NLP and text analytics and ML algorithms like clustering, regression, classification etc
  • Experience working with recommendation engines, data pipelines and distributed machine learning