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- Tasks: Lead the design and implementation of data systems and machine learning models.
- Company: Join a forward-thinking tech company focused on innovation and data-driven solutions.
- Benefits: Enjoy a competitive salary, excellent benefits, and hybrid work options.
- Why this job: Make a real-world impact in a collaborative environment that values data and innovation.
- Qualifications: Strong background in data science or ML engineering with advanced Python and SQL skills required.
- Other info: Opportunity to work with cutting-edge tools and technologies in a supportive team.
The predicted salary is between 43200 - 72000 £ per year.
Lead Data Science Engineer
Hybrid – 2 days a week
Competitive salary + excellent benefits
About the Role:
A forward-thinking tech company is seeking a Lead Data Science Engineer to join their growing data function. This is a strategic, hands-on role where you\’ll design and build modern data infrastructure, guide the deployment of machine learning models, and shape the delivery of data-driven products and APIs. You\’ll lead technical initiatives while working closely with data engineers, scientists, architects, and product stakeholders to ensure real-world impact through data.
What You\’ll Be Doing:
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Architect and implement scalable pipelines and data systems that power advanced analytics and ML applications
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Lead the rollout of data products, including APIs and secure data delivery mechanisms for clients and internal use
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Partner with cross-functional teams to align data solutions with wider business goals
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Take ownership of productionising ML models and integrating them into operational systems
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Improve access to data through the development of self-serve analytics tools
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Support data quality, privacy, and governance across platforms
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Explore emerging tools and methods to keep our stack future-ready
What We\’re Looking For:
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Strong background in data science or ML engineering , with leadership or senior-level experience
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Advanced skills in Python and strong fluency in SQL
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Experience working in cloud-based environments (preferably Azure)
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Hands-on experience with tools such as Postgres, Langchain, Ollama, Polars, GitLab CI/CD, and Unix-based systems
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Proven track record of deploying ML models into production and managing lifecycle
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Comfortable designing data services/APIs and supporting self-serve analytics platforms
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Solid understanding of data privacy regulations (e.g. GDPR), and best practice in security and governance
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Excellent communication skills and the ability to influence both technical and business audiences
Nice to Have:
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Familiarity with Docker, Kubernetes , or infrastructure automation tools like Ansible
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Agile experience and strong stakeholder presentation skills
Why Join?
You\’ll be working in a collaborative, purpose-driven environment where data is central to innovation. With the backing of a well-established organisation and the autonomy of a modern data team, you\’ll shape high-impact systems and products that make a difference to real users.
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Lead Data Science Engineer employer: Hewett Recruitment
Contact Detail:
Hewett Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Science Engineer
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, such as Postgres, Langchain, and GitLab CI/CD. Having hands-on experience or even personal projects showcasing these tools can set you apart during discussions.
✨Tip Number 2
Brush up on your Python and SQL skills, as these are crucial for the role. Consider working on small projects that involve data manipulation and machine learning to demonstrate your proficiency in these areas.
✨Tip Number 3
Prepare to discuss your experience with deploying ML models into production. Be ready to share specific examples of challenges you faced and how you overcame them, as this will showcase your problem-solving abilities.
✨Tip Number 4
Understand the importance of data privacy regulations like GDPR. Being able to articulate how you have implemented best practices in security and governance in past roles will demonstrate your commitment to responsible data management.
We think you need these skills to ace Lead Data Science Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data science and machine learning engineering. Focus on leadership roles and specific projects where you've designed data infrastructure or deployed ML models.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data-driven products and your ability to lead technical initiatives. Mention specific tools and technologies you’ve worked with that align with the job description, such as Python, SQL, and cloud environments.
Showcase Relevant Projects: Include examples of past projects in your application that demonstrate your skills in architecting scalable data systems and deploying ML models. Be specific about your role and the impact of these projects.
Highlight Communication Skills: Since excellent communication is key for this role, emphasise your ability to influence both technical and business audiences. Provide examples of how you've successfully collaborated with cross-functional teams in previous positions.
How to prepare for a job interview at Hewett Recruitment
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with Python, SQL, and cloud-based environments like Azure. Highlight specific projects where you've implemented scalable data pipelines or deployed machine learning models, as this will demonstrate your hands-on capabilities.
✨Demonstrate Leadership Skills
Since this role involves leading technical initiatives, be ready to share examples of how you've guided teams in previous positions. Discuss your approach to collaboration with cross-functional teams and how you align data solutions with business goals.
✨Understand Data Privacy Regulations
Familiarise yourself with GDPR and other data privacy regulations. Be prepared to discuss how you've ensured data quality and governance in past roles, as this is crucial for the position.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in deploying ML models or improving data access, and how you overcame them. This will showcase your critical thinking and adaptability.
