Responsibilities:
- Present complex findings to technical and non-technical stakeholders, displaying excellent communication skills
- Lead and Manage multiple data science projects simultaneously.
- Adapt to a fast-paced, evolving data-driven environment
- Tackle complex data challenges by taking a proactive and innovative approach to problem-solving
- Display strong ethical standards in data handling, model development, and result interpretation
Basic Requirements:
- Advanced degree (Ph.D. or Master's) plus 4+ years of non-academic professional experience
- Proficiency in Python or R (both preferred)
- SQL expertise
- Strong background in statistical methods, including: Regression analysis, Model testing, Logistic regression, Generalized Linear Models (GLM) and Solid understanding of statistics and random variables
- Technical Knowledge:
- Familiarity with one or more advanced machine learning techniques:
- Gradient Boosting Machines (GBM)
- K-means clustering
- Neural Networks
- Support Vector Machines (SVMs)
- Bayesian Networks
- Natural Language Processing (NLP)
- Experience with machine learning frameworks such as: TensorFlow, Scikit-learn, PyTorch and Kera
Other Characteristics:
- Team player and proven relationship-builder
- Strong interpersonal skills, high level of professionalism and integrity
- Excellent organizational and project management skills
- Experience handling multiple responsibilities, tasks, and projects in a fast-paced environment preferred
- A positive attitude that approaches tasks/projects from a hands-on, roll up your sleeves frame of mind
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