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For Companies At a Glance
- Tasks: Join our team to drive data insights in Private Equity and optimize investment decisions.
- Company: Be part of a leading firm in the Private Equity space, shaping investment strategies.
- Benefits: Enjoy a hybrid work model, competitive salary, bonuses, and great benefits.
- Why this job: Work closely with senior stakeholders and enhance your skills in a dynamic environment.
- Qualifications: 3-4+ years in Data Science, experience in Private Equity, and proficiency in Python and SQL.
- Other info: This role offers a unique chance to impact investment decisions directly.
The predicted salary is between 90000 - 210000 £ per year.
Job Description
Senior Data Scientist
London – Hybrid (4 days a week)
Up to £150,000 + bonus and benefits
This is a great opportunity for a Data Scientist to work in the Private Equity space, reporting directly into a Head of Data.
THE ROLE
In this role you will:
- Work on due diligence, reporting for investment teams in a data environment
- Build out and scale Machine Learning with Python and SQL
- Drive Data Visualisation with Tableau/Power BI
- Work on Cashflow predictive models to optimise investment decisions
- Be part of the front office investment team, working closely with senior stakeholders
Skills And Experience
- Candidates must have experience in Private Equity – preferably in a Data team
- Or experience in a strategy consultancy, ideally with a focus on PE projects
- MSc or BSc in a numerical or relevant field is preferred with 3-4+ years of experience
- Python and SQL experience is required
How To Apply
Please register your interest for this role by sending your CV to Kiran Ramasamy via the apply link on this page
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Senior Data Scientist - Private Equity employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist - Private Equity
✨Tip Number 1
Make sure to highlight your experience in Private Equity or strategy consultancy during your conversations. This will show that you understand the unique challenges and opportunities in this field.
✨Tip Number 2
Familiarize yourself with the latest trends in data science, especially in relation to Machine Learning and predictive modeling. Being able to discuss recent advancements can set you apart from other candidates.
✨Tip Number 3
Prepare to discuss specific projects where you've used Python and SQL to drive results. Concrete examples will demonstrate your technical skills and how they can benefit the investment team.
✨Tip Number 4
Engage with the company’s culture and values during your interactions. Showing that you align with their mission and are excited about contributing to the front office investment team can make a strong impression.
We think you need these skills to ace Senior Data Scientist - Private Equity
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in Private Equity and data science. Emphasize your skills in Python, SQL, and any experience with data visualization tools like Tableau or Power BI.
Craft a Strong Cover Letter: Write a cover letter that specifically addresses the role of Senior Data Scientist in Private Equity. Mention your experience with due diligence, predictive modeling, and working with senior stakeholders to demonstrate your fit for the position.
Showcase Relevant Projects: Include specific examples of projects you've worked on that relate to the responsibilities listed in the job description. Highlight your contributions to machine learning initiatives and any successful outcomes from your work.
Follow Application Instructions: Ensure you send your application through the provided link and address it to Kiran Ramasamy as specified. Double-check that all documents are attached and formatted correctly before submitting.
How to prepare for a job interview at Harnham
✨Showcase Your Private Equity Knowledge
Make sure to highlight your experience in the Private Equity space. Be prepared to discuss specific projects or roles where you've contributed to data-driven investment decisions.
✨Demonstrate Technical Proficiency
Since Python and SQL are crucial for this role, be ready to discuss your technical skills in detail. You might even be asked to solve a problem or explain your approach to a data challenge.
✨Prepare for Stakeholder Interaction
As you'll be working closely with senior stakeholders, practice articulating complex data insights in a clear and concise manner. Think about how you can translate technical findings into actionable business strategies.
✨Familiarize Yourself with Data Visualization Tools
Since the role involves driving data visualization with Tableau or Power BI, brush up on these tools. Be ready to discuss how you've used them in past projects to present data effectively.
