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- Tasks: Lead ML/AI initiatives and oversee end-to-end solutions in a dynamic team.
- Company: Join a market-leading Telecommunications company with a strong Data Science and AI team.
- Benefits: Enjoy a competitive salary, car allowance, bonus, and remote work flexibility.
- Why this job: Shape the future of data science while leading a talented team in an innovative environment.
- Qualifications: 5+ years in data science/ML with leadership experience; BSc/MSc preferred.
- Other info: Work remotely with just one day a month in Uxbridge.
The predicted salary is between 60000 - 84000 £ per year.
LEAD DATA SCIENTIST – Data Science/ML REMOTE – 1 day per month in Uxbridge Up to £100,000 + car allowance + bonus We are working with a market leading Telecommunications company with an established Data Science and AI team to bring a Lead Data Scientist into the team. They already have a strong established DS/ML team but are looking to grow this. Lead the vision and delivery of ML/AI initiatives across the business. Design and oversee end-to-end ML solutions, from experimentation through to production deployment Build a high-performing team of Data Scientists and ML Engineers. Provide strategic leadership on DS/ML capabilities and opportunities, ensuring alignment with key business goals and technical roadmaps Strong track record of deploying machine learning solutions. Experience in leading data science projects and managing data scientists and ML Engineers Experience with A/B testing and multivariate experimentation BSc or MSc in Computer Science, Data Science, or related field (preferred) 5+ years of experience in data science/ML with proven leadership experience Strong understanding of MLOps practices and production deployment requirements and job orchestration
Lead Health Data Scientist employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Health Data Scientist
✨Tip Number 1
Make sure to showcase your leadership experience in data science projects. Highlight specific instances where you've successfully led a team or initiative, as this role requires strong strategic leadership.
✨Tip Number 2
Familiarize yourself with the latest trends in MLOps and production deployment. Being able to discuss current best practices and how you've implemented them in past projects will set you apart from other candidates.
✨Tip Number 3
Prepare to discuss your experience with A/B testing and multivariate experimentation. Be ready to provide examples of how these methodologies have influenced your decision-making in previous roles.
✨Tip Number 4
Network with professionals in the telecommunications and data science fields. Engaging with industry peers can provide insights into the company culture and expectations, which can be beneficial during interviews.
We think you need these skills to ace Lead Health Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in leading data science projects and managing teams. Emphasize your strong track record of deploying machine learning solutions and any relevant MLOps practices you've implemented.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and AI. Discuss how your vision aligns with the company's goals and how you can contribute to their existing DS/ML team. Mention specific examples of past projects that demonstrate your leadership and technical skills.
Showcase Relevant Experience: When detailing your work experience, focus on your roles in A/B testing and multivariate experimentation. Provide concrete examples of how your contributions led to successful outcomes in previous positions.
Highlight Educational Background: If you have a BSc or MSc in Computer Science, Data Science, or a related field, make sure to mention it prominently. This is a preferred qualification, so showcasing it can strengthen your application.
How to prepare for a job interview at Harnham
✨Showcase Your Leadership Experience
Since the role requires strong leadership skills, be prepared to discuss your previous experiences in leading data science projects. Highlight specific examples where you successfully managed teams and delivered impactful ML solutions.
✨Demonstrate Technical Expertise
Make sure to brush up on your technical knowledge related to MLOps practices and production deployment. Be ready to explain your approach to designing end-to-end ML solutions and any relevant tools or frameworks you have used.
✨Discuss A/B Testing Experience
Given the emphasis on A/B testing and multivariate experimentation, prepare to share your experiences with these methodologies. Discuss how you've implemented them in past projects and the outcomes they produced.
✨Align with Business Goals
Understand the company's key business goals and think about how your expertise in data science can align with them. Be ready to discuss how you can contribute strategically to their DS/ML capabilities and initiatives.
