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- Tasks: Lead machine learning projects, mentor junior team members, and communicate insights effectively.
- Company: Join a forward-thinking company focused on leveraging data science for real-world impact.
- Benefits: Enjoy flexible working options, professional development opportunities, and a collaborative culture.
- Why this job: Make a difference by solving complex problems and shaping the future of data science.
- Qualifications: Experience in machine learning, proficiency in Python or R, and strong leadership skills required.
- Other info: Ideal for those passionate about AI and eager to drive innovation in a dynamic environment.
The predicted salary is between 48000 - 72000 £ per year.
Lead Machine Learning Engineer
This role is a senior-level position in data science, centered on applying machine learning to solve complex problems, drive project execution, and mentor team members. The successful candidate will lead and actively contribute to initiatives that leverage advanced analytics to deliver tangible, real-world outcomes.
Responsibilities
- Communicate data-driven insights and strategic recommendations to clients and internal stakeholders in a clear, actionable manner.
- Design and implement predictive models using advanced analytics, including techniques in machine learning, natural language processing (NLP), computer vision, and optimization.
- Oversee the full lifecycle of multiple data science projects, ensuring effective resource management, resolution of technical challenges, and streamlined code review processes.
- Provide mentorship and guidance to junior data scientists and analysts, supporting their technical growth and professional development.
- Contribute to business development activities by supporting proposal creation and demonstrating the value of data science capabilities to potential clients.
- Partner with data engineering teams to ensure seamless integration of analytics solutions within client environments.
- Collaborate with leadership to shape the roadmap for data science initiatives and ensure alignment with strategic objectives.
Required Experience
- Demonstrated experience in developing and evaluating machine learning and AI solutions within commercial or client-facing environments.
- Proficiency in Python or R, with hands-on application of supervised and unsupervised learning methods, as well as more advanced modeling techniques.
- Strong ability to distill complex technical findings into language that resonates with business audiences.
- Proven leadership in managing project teams and navigating challenges posed by large, unstructured, or messy datasets.
- Experience in consulting, proposal development, and strategic project planning.
Desired Skills and Experience
LLM, NLP, Consulting
Machine Learning Engineer employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network with professionals in the machine learning field. Attend industry conferences, webinars, or local meetups to connect with others who work in data science. This can help you learn about job openings and gain insights into what companies like us at StudySmarter are looking for.
✨Tip Number 2
Showcase your projects on platforms like GitHub or Kaggle. Having a portfolio of your machine learning projects can demonstrate your skills and experience effectively. Make sure to highlight any projects that involve NLP or computer vision, as these are particularly relevant to our role.
✨Tip Number 3
Prepare to discuss your leadership experiences in detail. Since this is a senior-level position, be ready to share examples of how you've mentored others or led project teams. This will show us that you have the necessary skills to guide junior team members and manage complex projects.
✨Tip Number 4
Familiarise yourself with our company’s values and recent projects. Understanding our mission and how we apply machine learning can help you tailor your conversations during interviews. It shows genuine interest and can set you apart from other candidates.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning and data science. Focus on specific projects where you've applied advanced analytics, and mention any leadership roles or mentoring experiences.
Craft a Compelling Cover Letter: In your cover letter, clearly articulate your passion for machine learning and how your skills align with the responsibilities of the role. Mention specific techniques you’ve used, such as NLP or computer vision, and how they can benefit the company.
Showcase Your Projects: If applicable, include links to your GitHub or portfolio showcasing your machine learning projects. Highlight any predictive models you've designed and implemented, especially those that have delivered real-world outcomes.
Prepare for Technical Questions: Anticipate technical questions related to machine learning algorithms and project management. Be ready to discuss your approach to solving complex problems and how you mentor junior team members.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning algorithms, particularly in Python or R. Bring examples of projects where you've implemented predictive models and be ready to explain the techniques you used and the outcomes achieved.
✨Communicate Clearly
Since the role involves communicating complex data-driven insights, practice explaining your past projects in simple terms. Tailor your explanations to resonate with business audiences, highlighting how your work has delivered tangible results.
✨Demonstrate Leadership Experience
Highlight any previous experience leading project teams or mentoring junior staff. Be ready to share specific examples of how you've navigated challenges in data science projects and supported team members in their professional growth.
✨Prepare for Business Development Questions
Expect questions about your experience in consulting and proposal development. Think of instances where you've contributed to business development activities and be ready to discuss how you can demonstrate the value of data science capabilities to potential clients.
