The job requires a Data Science Manager to lead the delivery of advisory services to high-growth organizations, manage a diverse team, and pursue new data science opportunities. The role involves client communication, data analysis, and model maintenance. The ideal candidate has significant data analysis experience, leadership skills, and experience working in the energy and resources sector.
Requirements
- Significant data analysis experience using Python
- 5+ years relevant work experience with applying analytics or working with data
- Experience working in the energy and resources sector
- Leadership or management experience, including project management, in an analytical or data-driven field
- Experience with optimization modelling, machine learning, forecasting, natural language processing, and generative AI tools
- Experience with Cloud ML (AWS, GCP, Azure), or similar tools is an asset
- Strong experience with statistical analytical techniques, data mining, and predictive models
- Database and programming experience with data manipulation and integration skills using (one or more of) SQL, Oracle, Hadoop, NoSQL Databases, or similar tools
- Ability to understand business significance of the data, work with data with significant ambiguity, develop creative approaches to analytical problems, and interpret data and results from a business/industry perspective
- Enthusiastic about solving complex problems with a variety of analytical tools
- Professional services, consulting, or advisory experience is an asset
- Strong oral and written communication skills
- Interest in continuing to develop analytical and business development skills
- Advanced degree (MSc, equivalent or higher) in Statistics, Mathematics, Physics, Computer Science, or related field is required
Benefits
- Competitive base salary and variable pay opportunities
- Total Rewards Package that extends well beyond traditional compensation and benefit programs
- Mental health support benefits
- Flexible benefit spending account
- Deloitte Days (firm-wide closures)
- Development and Innovation Days (dedicated days for learning)
- Flexible work arrangements
- Hybrid work structure
