At a Glance
- Tasks: Lead a team of data scientists to develop advanced models for fraud detection and performance insights.
- Company: Join a growing, innovative company in the AdTech/SaaS space focused on data excellence.
- Benefits: Enjoy a competitive salary, flexible working options, and a collaborative team environment.
- Why this job: Shape the future of data science while making a real impact in advertising campaigns.
- Qualifications: Ph.D. or Master’s in a relevant field with substantial experience in data science leadership.
- Other info: Stay ahead of industry trends and work with cutting-edge machine learning technologies.
The predicted salary is between 43200 - 72000 £ per year.
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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Contact Detail:
Creo Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Data Science
✨Tip Number 1
Network with professionals in the data science field, especially those who have experience in AdTech or SaaS. Attend industry conferences, webinars, and meetups to connect with potential colleagues and learn about the latest trends and challenges in the sector.
✨Tip Number 2
Showcase your leadership skills by sharing examples of how you've successfully mentored teams or led projects in your previous roles. Highlight your ability to foster a collaborative culture and drive data-driven decision-making within an organisation.
✨Tip Number 3
Stay updated on the latest machine learning technologies and frameworks. Being knowledgeable about tools like TensorFlow, PyTorch, and cloud platforms such as AWS or Azure will demonstrate your commitment to staying at the forefront of the industry.
✨Tip Number 4
Prepare to discuss how you would align data science initiatives with business goals. Think about specific examples where you've successfully leveraged data to solve business problems and be ready to share these insights during interviews.
We think you need these skills to ace Head of Data Science
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data science leadership, machine learning applications, and any relevant projects. Use specific examples that demonstrate your ability to lead teams and deliver data-driven solutions.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and your vision for leading a team. Mention how your skills align with the company's goals and how you can contribute to their success in the AdTech/SaaS space.
Showcase Technical Skills: Clearly outline your proficiency in Python, machine learning frameworks, and data engineering tools. Provide examples of how you've used these skills in previous roles to solve complex problems or improve processes.
Prepare for Interviews: Be ready to discuss your leadership style and how you mentor and develop team members. Prepare to share insights on industry trends and how you would approach data science projects within the company.
How to prepare for a job interview at Creo Recruitment
✨Showcase Your Leadership Skills
As a Head of Data Science, you'll be expected to lead and mentor a team. Be prepared to discuss your previous leadership experiences, how you've developed teams, and the strategies you've used to foster collaboration and innovation.
✨Demonstrate Technical Expertise
Make sure to highlight your proficiency in machine learning frameworks and data engineering tools. Be ready to discuss specific projects where you've implemented advanced statistical models or machine learning algorithms, and how they delivered business value.
✨Communicate Clearly with Non-Technical Stakeholders
Since part of your role involves educating non-technical team members, practice explaining complex data concepts in simple terms. Prepare examples of how you've successfully communicated insights to stakeholders in the past.
✨Align Data Science with Business Goals
Be ready to discuss how you've previously aligned data science initiatives with broader business objectives. Share examples of impactful projects you've prioritised and how they contributed to the overall success of the organisation.