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- Tasks: Lead impactful machine learning projects for private equity portfolios and manage end-to-end delivery.
- Company: A top AI firm in the UK focused on investment solutions.
- Benefits: Hybrid work model, competitive salary, pension scheme, and private medical cover.
- Why this job: Make a real impact with data-driven projects in a dynamic investment environment.
- Qualifications: Experience in machine learning and strong collaboration skills with stakeholders.
- Other info: Join a diverse team and grow your career in an innovative field.
The predicted salary is between 43200 - 72000 £ per year.
A leading investment-focused AI firm in the UK is looking for a Senior Data Scientist to work on impactful machine learning solutions within private equity portfolio companies. This role involves managing end-to-end ML delivery and collaborating closely with senior stakeholders to ensure commercial viability.
The position offers a hybrid working model, competitive benefits including employer pension and private medical cover, and a focus on diverse data-driven projects.
Senior Data Scientist — ML for Private Equity Portfolios (Hybrid, London) employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist — ML for Private Equity Portfolios (Hybrid, London)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those already working in private equity or data science. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Showcase your skills! Prepare a portfolio of your best machine learning projects that demonstrate your ability to deliver impactful solutions. This will help you stand out when discussing your experience with potential employers.
✨Tip Number 3
Practice your pitch! Be ready to explain how your past experiences align with the role of Senior Data Scientist. Focus on your end-to-end ML delivery and how you've collaborated with stakeholders to drive commercial success.
✨Tip Number 4
Apply through our website! We make it easy for you to submit your application directly, ensuring it gets the attention it deserves. Plus, you'll be part of a community that values diverse, data-driven projects.
We think you need these skills to ace Senior Data Scientist — ML for Private Equity Portfolios (Hybrid, London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning and data science. We want to see how your skills align with the role, so don’t be shy about showcasing your past projects and achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about working with private equity portfolios and how your expertise can contribute to our mission. Keep it engaging and personal.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled complex data challenges in the past. We love seeing candidates who can think critically and deliver impactful solutions, so let us know how you’ve made a difference!
Apply Through Our Website: We encourage you to apply directly 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 from us!
How to prepare for a job interview at Harnham
✨Know Your ML Inside Out
Make sure you brush up on your machine learning concepts and techniques. Be ready to discuss your previous projects in detail, especially those that relate to private equity portfolios. This will show your depth of knowledge and how you can apply it to their specific needs.
✨Understand the Business Context
Research the firm and its portfolio companies. Understand how machine learning can drive value in private equity. Being able to connect your technical skills with their business goals will impress the interviewers and demonstrate your strategic thinking.
✨Prepare for Stakeholder Engagement
Since the role involves collaborating with senior stakeholders, practice articulating complex data science concepts in a way that's easy to understand. Think about how you can communicate your ideas clearly and effectively, as this will be crucial in ensuring commercial viability.
✨Showcase Your Adaptability
With a hybrid working model, it's important to highlight your ability to work both independently and as part of a team. Share examples of how you've successfully navigated remote collaboration and maintained productivity, as this will resonate well with their working style.
