Head of Data Science

This range is provided by Creo Recruitment. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range Head of Data Science - AdTech/SaaS/Fraud or Anomaly Detection
Job Summary :
We seek an experienced and visionary Head of Data Science to join our growing team. In this role, you will bring thought leadership and promote a culture of data excellence by leveraging our data assets to develop advanced data models for identifying fraudulent behaviour and surfacing performance insights within our clients' advertising campaigns.
You will communicate and educate the organisation on all things data and data science so you must have a desire to present, collaborate and coach non-technical organisational team members. You will have strong experience in machine learning applications in highly scalable transactional systems and oversight of their implementation and delivery into client-facing applications. You will have extensive experience in creating and promoting a collaborative culture of data-driven decisions, leading by example a team of data scientists & data analysts.
Key Responsibilities :
Lead and mentor a growing team of data scientists and analysts, providing technical guidance and career development support.
Hire, mentor and manage a data science and data analyst team to ensure we have a clear vision of its data and how to maximise its usage.
Lead complex data science projects, offering guidance on model development, deployment, and optimisation.
Establish best practices in machine learning, statistical analysis, and model governance.
Responsible for the design and performance of our algorithmic approaches.
Design and implement advanced statistical models and machine learning algorithms to solve complex problems.
Collaborate with the wider Product and Technology teams and broader internal stakeholders across the business to understand market issues and identify opportunities where data science can deliver business value.
Oversee the development and deployment of scalable data models.
Monitor and evaluate the performance of our machine-learning models.
Develop frameworks to assess and mitigate risks associated with data biases, model inaccuracies, and operational failures.
Stay at the forefront of industry trends and machine learning technologies.
Communicate insights and progress to non-technical stakeholders in a clear and actionable manner.
Requirements :
Substantial experience in data science, with experience in a leadership or management role.
Experience understanding key stakeholder needs and leveraging our core data assets to solve business problems across internal and external use cases.
Proven track record of delivering data-driven solutions from conception to delivery.
Ph.D. or Master’s Degree in a relevant field (e.g., Computer Science, Statistics, Mathematics, Engineering, or Data Science).
Experience in aligning data science initiatives with business goals and prioritising impactful projects.
Platform-agnostic approach to machine learning technologies.
Proficiency in Python.
Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch, XGBoost).
Strong knowledge of data engineering tools and technologies (e.g., Spark, Hadoop, SQL).
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Understanding of industry regulations, compliance, and ethical considerations (e.g., GDPR, HIPAA, data ethics).
Exceptional communication and presentation skills, with the ability to influence stakeholders.
Experience building dashboards and insights using BI tools such as Tableau or Quicksight.
Experience in designing team goals and workstreams and aligning them with organisational objectives.
Why Join Us?
Be part of a growing, innovative company with a dynamic and collaborative team.
Opportunity to shape and influence the people function in a scaling organisation.
Competitive salary and benefits package, including flexible working options.
Seniority level Mid-Senior level
Employment type Full-time
Job function Engineering and Information Technology
Industries Advertising Services and Data Infrastructure and Analytics

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