At a Glance
- Tasks: Lead a team to maintain and enhance production ML models for a customer-facing product.
- Company: Dynamic tech company focused on data science innovation.
- Benefits: Competitive daily rate, flexible working, and opportunities for mentorship.
- Other info: Collaborative culture with a focus on continuous improvement and stakeholder engagement.
- Why this job: Make a real impact by leading a talented team in a thriving environment.
- Qualifications: Strong NLP and machine learning experience, plus leadership skills.
The predicted salary is between 46800 - 46800 £ per year.
£600/day (Inside IR35)
6 Months contract
Flexible UK working with occasional onsite presence in London, Birmingham or Basingstoke
I'm currently supporting a client looking for a hands-on Lead Data Scientist to take ownership of an established data science capability operating within a live customer-facing product. This is not a greenfield build. The priority is ensuring continuity, stability and value delivery from existing production machine learning models while providing technical leadership to a small team.
You'll be responsible for:
- Owning and maintaining production ML models
- Providing technical oversight and quality assurance
- Supporting and mentoring two junior Data Scientists
- Defining model monitoring, alerting and retraining processes
- Translating technical outputs into business value for stakeholders
- Working closely with product, engineering, analytics and business teams
Current environment:
- Databricks
- Customer-facing product platform
- NLP model processing structured and unstructured data
- Ensemble-based predictive model forecasting performance and longevity outcomes
We're looking for someone with:
- Strong NLP and supervised machine learning experience
- Experience managing production-grade ML systems
- MLOps and model lifecycle management expertise
- Previous experience leading or mentoring Data Scientists
- Excellent stakeholder engagement and communication skills
This would suit a Senior or Lead Data Scientist who enjoys balancing hands-on technical work with team leadership and business engagement.
If you're interested, or know someone who could be a good fit, please get in touch.
Lead Data Scientist in London employer: MBN Solutions
Join a forward-thinking organisation that values innovation and collaboration, offering a dynamic work culture where your expertise as a Lead Data Scientist will directly impact customer-facing products. With flexible working arrangements across the UK and opportunities for professional growth through mentoring junior team members, you'll thrive in an environment that prioritises both technical excellence and meaningful contributions to business outcomes.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field and let them know you're on the lookout for opportunities. You never know who might have a lead or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous projects, especially those involving NLP and machine learning. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss how you've led teams and delivered value through your work. Practice makes perfect!
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and experience. Plus, it shows you're serious about joining our team.
We think you need these skills to ace Lead Data Scientist in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with NLP and supervised machine learning. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects you've worked on!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for the Lead Data Scientist role. Mention your experience in managing production ML systems and how you’ve successfully led teams in the past.
Showcase Your Technical Skills:In your application, be specific about your technical expertise, especially in MLOps and model lifecycle management. We love seeing concrete examples of how you've provided technical oversight and quality assurance in previous roles.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Don’t miss out!
How to prepare for a job interview at MBN Solutions
✨Know Your Models Inside Out
Make sure you can discuss the production ML models you'll be working with. Be prepared to explain how they function, their strengths and weaknesses, and how you would ensure their stability and continuity. This shows you’re not just a hands-on techie but also someone who understands the bigger picture.
✨Showcase Your Leadership Skills
Since this role involves mentoring junior Data Scientists, be ready to share examples of your previous leadership experiences. Talk about how you've supported team members in the past and how you plan to foster their growth. This will demonstrate your capability to lead while still being technically proficient.
✨Communicate Like a Pro
You’ll need to translate technical outputs into business value, so practice explaining complex concepts in simple terms. Think about how you would communicate with stakeholders from different backgrounds. Clear communication is key, so don’t shy away from showcasing your interpersonal skills during the interview.
✨Familiarise Yourself with the Tools
Get comfortable with the tools mentioned in the job description, like Databricks and any relevant NLP frameworks. If you have experience with ensemble-based predictive models, be ready to discuss them. Showing that you’re up-to-date with the current environment will give you an edge over other candidates.
