Data Science & ML coding assessments on CodeSubmit
Hire Data Scientists & Machine Learning Engineers with Confidence
Let your candidates showcase their data chops with full support for Jupyter notebooks, Python, R, PyTorch, TensorFlow, Spark, and Julia.
Real-World Scenarios to Evaluate Data Science Competence
Refine Your Hiring Process with Data-Driven Assessments
Enhance your recruitment approach by utilizing CodeSubmit's Jupyter Support, enabling candidates to demonstrate their expertise in a practical, real-world context. Assess proficiency in a range of technologies including Python, R, and various machine learning frameworks, ensuring a comprehensive evaluation of skills.
Our platform facilitates an environment that mirrors real-world challenges, allowing you to gauge the practical abilities of candidates effectively and make informed hiring decisions.
Jupyter Minimal: Utilize a JupyterLab environment to enable candidates to work on notebooks collaboratively, ensuring a focus on practical skills.
Jupyter SciPy: Access a JupyterLab setup with SciPy to provide a robust assessment environment, incorporating key Python scientific packages.
Jupyter TensorFlow: Evaluate candidates on machine learning model development within a JupyterLab environment equipped with TensorFlow.
Assess Proficiency in R, PyTorch, and Julia
Advanced Evaluation with Specialized Tools
Jupyter R: Provide an environment where candidates can showcase their R programming skills, complete with essential packages.
Jupyter PyTorch: Offer a platform for candidates to demonstrate their knowledge in deep learning, using a PyTorch-based JupyterLab environment.
Jupyter Julia: Enable candidates to exhibit their technical computing abilities with Julia in a high-performance JupyterLab setting.