What are the responsibilities and job description for the Data Scientist position at Maddisoft?
Job Details
Maddisoft has the following immediate opportunity, let us know if you or someone you know would be interested. Send in your resume ASAP. - U.S. Citizens and those authorized to work in the U.S. are encouraged to apply. Looking for W2 CONTRACT, Send in resume along with LinkedIn profile without which applications will not be considered. Call us NOW! ***Visa sponsorship is available for this position.***
Job Title: Data Scientist
Job Location: Princeton, NJ- Hybrid 3days/week
Essential Duties/Responsibilities:
Understanding of machine learning and deep learning models to select and implement for prediction, classification, and clustering
Understanding of the business context of projects and able to identify areas where models will be less predictive or have caveats to their predictive powers
Ability to communicate and establish good relations with multi-disciplinary teams
Expertise with neural networks, specifically RNNs within the Keras/TensorFlow framework.
Proficiency with Python, including pandas, scikit-learn
Experience in PySpark
Minimum Requirements:
Bachelor's degree in a quantitative field, such as Statistics, Mathematics, Computer Science, Economics, Engineering, or Operations Research required.
3 years of experience in statistical modeling and quantitative analysis in industry or full-time academic research
Preferred Qualifications:
Advanced Degree (MS or PhD) in Statistics, Mathematics or Quantitative Marketing with a focus on machine learning is strongly preferred.
Additional Knowledge, Skills and Abilities:
Knowledge of power transformers, experience with electrical engineering.
Prior experience predictive maintenance in a power or manufacturing environment.
Experience with Databricks, AWS SageMaker and/or Google Vertex AI
Comfortable working in Linux
Experience with Git
Experience with Docker containers
Good communication skills
Keen attention to details
Think critically about analyses to ensure the conclusions make sense before sharing