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- Tasks: Lead complex data science projects and deliver innovative solutions for clients.
- Company: Dynamic data consultancy firm in the UK with a focus on client success.
- Benefits: Hybrid work environment, competitive salary, and extensive professional development opportunities.
- Why this job: Make a real impact by solving complex data challenges with cutting-edge technology.
- Qualifications: 5+ years in data science, machine learning expertise, and proficiency in Python and AWS.
- Other info: Collaborative culture that values innovation and growth.
The predicted salary is between 43200 - 72000 £ per year.
A data consultancy firm in the UK seeks an experienced Data Science Consultant to lead complex projects while delivering innovative solutions. You will collaborate closely with clients, identify their data science needs, and apply best practices in data engineering and analysis.
The ideal candidate has over 5 years of experience in data science, machine learning, and is skilled in Python and cloud platforms like AWS. This role offers a hybrid work environment and numerous professional development opportunities.
Lead Data Scientist — Client-Facing ML & Data Solutions in London employer: Daintta
Contact Detail:
Daintta Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist — Client-Facing ML & Data Solutions 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 refer you to a great role.
✨Tip Number 2
Showcase your skills! Create a portfolio that highlights your best projects, especially those involving machine learning and data solutions. 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 common data science scenarios and case studies. Practice explaining your thought process clearly, as clients will want to see how you tackle real-world problems.
✨Tip Number 4
Don't forget to apply through our website! We have loads of exciting roles that could be perfect for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Lead Data Scientist — Client-Facing ML & Data Solutions in London
Some tips for your application 🫡
Show Off Your Experience: Make sure to highlight your 5+ years of experience in data science and machine learning. We want to see how you've tackled complex projects and delivered innovative solutions, so don’t hold back!
Tailor Your Application: Customise your CV and cover letter to reflect the specific skills mentioned in the job description, like Python and AWS. This shows us that you’ve done your homework and are genuinely interested in the role.
Be Client-Focused: Since this role involves collaborating closely with clients, share examples of how you've identified client needs and delivered tailored data solutions. We love seeing candidates who can bridge the gap between technical skills and client relationships!
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. Plus, it’s super easy!
How to prepare for a job interview at Daintta
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially in machine learning and Python. Be ready to discuss specific projects you've worked on, the challenges you faced, and how you overcame them. This will show your depth of knowledge and practical experience.
✨Understand the Client's Needs
Before the interview, research the consultancy firm and their clients. Think about how your skills can address their specific data science needs. Being able to articulate how you can provide tailored solutions will set you apart from other candidates.
✨Showcase Your Collaboration Skills
Since this role involves working closely with clients, be prepared to share examples of how you've successfully collaborated with others in past projects. Highlight your communication skills and how you’ve managed client expectations to deliver results.
✨Familiarise Yourself with Cloud Platforms
Given the emphasis on cloud platforms like AWS, make sure you’re comfortable discussing your experience with these technologies. If you have any relevant certifications or projects, mention them to demonstrate your expertise and readiness for the hybrid work environment.
