Data Scientist - Machine Learning

We're looking for a skilled Data Scientist to apply machine learning, clustering, and forecasting techniques to analyse large datasets, build predictive models, and support business objectives. You'll collaborate with cross-functional teams, deploy models into production, and create compelling visualizations to communicate insights. You will have a degree in a quantitative field, strong Python skills, experience with machine learning frameworks (e.g., TensorFlow, scikit-learn), and proficiency in data visualization tools like Power BI. Familiarity with big data and cloud technologies is a plus. Travel to Windsor will be required on occasion.

Key responsibilities will include:

• Data Analysis and Modelling: Apply machine learning, clustering and forecasting techniques to analyse large datasets and extract meaningful patterns and insights. Develop predictive models and algorithms to support business objectives.

• Data Exploration and Visualization: Explore and pre-process raw data to uncover trends, anomalies, and patterns. Create clear and compelling visualizations to communicate findings to both technical and non-technical stakeholders.

• Collaboration: Work closely with cross-functional teams, including business analysts and IT professionals, to understand business requirements and formulate data-driven solutions. Collaborate with domain experts to integrate domain knowledge into analytical models.

• Model Deployment: Implement and deploy machine learning models into production environments. Monitor and optimize model performance over time.

• Continuous Learning: Stay current with industry trends, emerging technologies, and best practices in data science and machine learning. Apply new methodologies and technologies to improve existing processes and solutions.

Here's what we're looking for:

• Bachelor's or master's degree in data science, Computer Science, Statistics, or a related quantitative field.

• Proficiency in programming languages such as Python for data analysis and modelling.

• Strong understanding of statistical concepts and experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).

• Experience with data visualization tools (e.g., Power BI, plotly, matplotlib).

• Experience with big data and cloud technologies (e.g., DataBricks, Azure, Spark) is a plus.

• Excellent problem-solving and analytical skills with a keen attention to detail.

• Effective communication skills, with the ability to present complex findings to both technical and non-technical audiences.