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- Tasks: Lead the development of data-driven solutions and deploy machine learning models.
- Company: Dynamic financial services organisation focused on enhancing data and AI capabilities.
- Benefits: Competitive salary, mentorship opportunities, and a clear path to leadership.
- Why this job: Make a real impact while mentoring others in a supportive team environment.
- Qualifications: Strong Python skills and experience in commercial data science applications.
- Other info: Opportunity for career growth and ownership of impactful projects.
The predicted salary is between 43200 - 72000 £ per year.
A financial services organization is looking for a Senior Data Scientist to enhance its data and AI capabilities. This hands-on role involves working with stakeholders to develop data-driven solutions, deploying machine learning models, and mentoring junior team members. You will have a clear path to leadership over the next one to two years, own impactful projects, and work within a supportive team.
Candidates should have strong Python skills and experience in commercial applications of data science.
Senior Data Scientist: Hands-on ML Leader in Production employer: Sanderson
Contact Detail:
Sanderson Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist: Hands-on ML Leader in Production
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or attend industry meetups. It’s all about making connections that can help us get our foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects and data-driven solutions. This will give us a chance to demonstrate our hands-on experience and creativity.
✨Tip Number 3
Prepare for the interview by brushing up on common data science scenarios. We should be ready to discuss how we’ve deployed models and mentored others, as these are key aspects of the role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure our application gets noticed. Plus, it shows we’re genuinely interested in being part of the team.
We think you need these skills to ace Senior Data Scientist: Hands-on ML Leader in Production
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your strong Python skills in your application. We want to see how you've used Python in real-world projects, especially in commercial applications of data science.
Talk About Your Hands-On Experience: Since this is a hands-on role, share specific examples of how you've developed and deployed machine learning models. We love seeing practical experience that aligns with our needs!
Mentorship Matters: If you've mentored junior team members before, let us know! We value leadership potential and want to hear about how you've helped others grow in their data science journey.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Sanderson
✨Showcase Your Python Prowess
Make sure to highlight your strong Python skills during the interview. Be ready to discuss specific projects where you've used Python for data science, especially in deploying machine learning models. This will demonstrate your hands-on experience and technical expertise.
✨Prepare for Stakeholder Scenarios
Since this role involves working closely with stakeholders, think of examples where you've successfully collaborated with non-technical teams. Prepare to discuss how you translated complex data insights into actionable strategies that benefited the business.
✨Mentorship Matters
As a potential mentor for junior team members, be prepared to talk about your experience in guiding others. Share specific instances where you've helped someone grow their skills or overcome challenges, showcasing your leadership potential.
✨Impactful Projects to Discuss
Identify a few impactful projects you've worked on that align with the company's goals. Be ready to explain your role, the challenges faced, and the outcomes achieved. This will illustrate your ability to own projects and deliver results in a supportive team environment.
