At a Glance
- 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 Up to £120,000 London (Hybrid, 3 days onsite per week) They are reinventing car finance for the digital age to make it faster, fairer, and more flexible for everyone. As a tech-first company, data is at the heart of everything they do – from real-time decisioning and risk modelling to personalising the customer journey and driving smarter business decisions. They are building a modern data stack and scaling our analytics capabilities to fuel innovation across the business. Analyse ways to increase acceptance rates while maintaining performance Identify data and algorithmic opportunities to reduce fraud risk Own the Collections strategy and deliver solutions to improve debt recovery Create analytic testing frameworks MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Expert in Python, R, SQL and a range of ML techniques (e.g., random forests, neural nets, reinforcement learning) A good understanding of the regulatory environment, especially responsible lending (creditworthiness/ affordability) Experience in using the latest data science techniques to enhance decisioning Strong background in risk management
Lead Data Scientist - Full Time employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist - Full Time
✨Tip Number 1
Make sure to showcase your leadership experience in data science projects. Highlight specific instances where you led a team or initiative, as this role requires strong strategic leadership.
✨Tip Number 2
Familiarize yourself with the latest MLOps practices and tools. Being able to discuss how you've implemented these in past projects will demonstrate your readiness for overseeing end-to-end ML solutions.
✨Tip Number 3
Prepare to discuss your experience with A/B testing and multivariate experimentation. This is crucial for the role, so having concrete examples ready will set you apart from other candidates.
✨Tip Number 4
Research the telecommunications industry and understand how data science can drive business goals within it. Showing that you have insights into the sector will demonstrate your alignment with the company's objectives.
We think you need these skills to ace Lead Data Scientist - Full Time
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 achievements in A/B testing and multivariate experimentation. Provide metrics or outcomes from your previous roles to illustrate your impact on business goals.
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 will help establish your foundational knowledge and credibility in the field.
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 a team 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 would ensure that ML initiatives support the overall strategy of the organization.