- Partner with engineers, product managers, and business partners to identify algorithmic problems, brainstorm possible approaches, and recommend the best path forward.
- Develop algorithms iteratively, building in the right level of complexity to solve the business problem at hand and support future improvements.
- Define success criteria for your models so that you can measure impact and changes over time. You'll be expected to communicate findings and drive continuous improvements.
- Collaborate with Software Engineers to implement algorithms in production that scale gracefully.
- Collaborate with stakeholders to prioritize projects and define requirements.
- Carry out analysis of data produced by our hardware systems and create insightful visualizations to share your findings.
- Contribute to internal libraries to help other teams with their data science needs including visualization, prediction, optimization, and inference.
- Advanced proficiency with Python and libraries commonly used for data analysis, e.g., Pandas, NumPy, SciPy, and Matplotlib.
- Strong understanding of data modeling and statistical analysis.
- Knowledge of optimization and predictive modeling techniques and experience applying them to real-world problems.
- Skilled at translating a general question or problem into a clearly defined algorithmic solution.
- Ability to communicate clearly with both technical and non-technical audiences.
- Ability to work independently and manage multiple projects simultaneously.
- 1-year Experience with Data Bricks or PySpark
- 1 year Experience with product ionizing data models
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Junior Data Scientist - Philadelphia, United States - Patterned Learning AI
Description
Job Description
Junior Data Scientist- Remote Job, 1+ Year Experience
Annual Income: $60K - $65K, Onsite
A valid work permit is necessary in the US/Canada
About us: Patterned Learning is a platform that aims to help developers code faster and more efficiently. It offers features such as collaborative coding, real-time multiplayer editing, and the ability to build, test, and deploy directly from the browser. The platform also provides tightly integrated code generation, editing, and output capabilities.
Responsibilities:
Patterned Learning can provide intelligent suggestions, automate repetitive tasks, and assist developers in writing code more effectively. This can help reduce coding errors, improve productivity, and accelerate the development process.
The pattern recognition is particularly relevant in the context of coding. Neural networks, especially deep learning models, are commonly employed for pattern detection and classification tasks.
These models simulate human decision-making and can identify patterns in data, making them well-suited for tasks like code analysis and generation.