Head of Data Science
- Lead and manage the flexible Data Science delivery teams (pods), ensuring alignment with business objectives and fostering a culture of innovation, collaboration, and continuous learning.
- Strategy delivery: Execute the AI Strategy, setting clear goals and priorities in line with business needs and company vision.
- End-to-end development: Own the end-to-end development of AI initiatives, from concept to validation of the AI solution with the business, ensuring the delivery of actionable insights that drive business impact.
- AI Solution Deployment: Work with Head of ML Engineering to ensure that AI solution deployments are on track and are consistent with business expectations.
- Cross-functional collaboration: With senior leadership, platform, engineering, and operations teams to understand needs and translate into action plans.
- Model Development: Oversee the creation of predictive models, machine learning algorithms, and data-driven insights that solve complex business challenges.
- Thought Leadership: Stay ahead of industry trends in data science and AI (including Generative AI) to implement cutting-edge technologies and techniques.
- 10+ years of experience in data science or equivalent, with at least 5 years in a leadership or management role. Advanced degree (Master’s or Ph.D.) in a quantitative field such as Data Science, Computer Science, Statistics, or Mathematics is preferred.
- Leadership:Demonstrated experience in overseeing multiple teams comprising technical specialists (including data scientists, machine learning engineers, data engineers) as well as functional specialists (e.g. product owners).
- Communication & Stakeholder Management: Demonstrated ability to influence and collaborate with cross-functional teams and senior stakeholders, including technical and non-technical colleagues.
- Utility expertise: Strong track record in the regulated utility space, ideally at an IOU.
- Functional expertise in data science, statistical modelling, data analysis, and AI techniques.
- Programming: Proficiency in Python and SQL.
- Data Insights:Deep knowledge of data manipulation, data visualization, and data wrangling with experience in tools like, Power BI.
- Cloud Platform: Hands-on experience – preferably with Azure (AWS and GCP also considered).
- Business Process:Strong understanding of business processes within at least one of the following domains: gas and electric operations, finance, customer experience, HR, legal and compliance, with the ability to translate business problems into data-driven solutions.
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