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For Companies At a Glance
- Tasks: Join our team to drive data insights in Private Equity, using Python and SQL.
- Company: Be part of a dynamic investment firm focused on innovative data solutions.
- Benefits: Enjoy a hybrid work model, competitive salary, bonuses, and great perks.
- Why this job: Make an impact in investment decisions while collaborating with senior stakeholders.
- Qualifications: 3-4+ years in data roles, preferably in Private Equity; MSc/BSc in a relevant field.
- Other info: This role offers a unique chance to work closely with the front office investment team.
The predicted salary is between 90000 - 210000 £ per year.
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
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 specific data tools mentioned in the job description, like Python, SQL, Tableau, and Power BI. Being able to discuss your proficiency with these tools will set you apart.
✨Tip Number 3
Prepare to discuss your previous projects related to cash flow predictive models. Be ready to explain how your work has optimized investment decisions in the past.
✨Tip Number 4
Since you'll be working closely with senior stakeholders, practice articulating complex data insights in a clear and concise manner. This will demonstrate your ability to communicate effectively within a front office investment team.
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 your experience in Private Equity and any relevant data projects. Emphasize your skills in Python, SQL, and 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, cashflow predictive models, and working with senior stakeholders.
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 data-driven decision-making.
Follow Application Instructions: Ensure you send your application through the provided link and address it to Kiran Ramasamy. Double-check that your documents are formatted correctly and free of errors before submission.
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 during the interview. Be prepared to discuss specific projects you've worked on and how your data skills contributed to 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 building machine learning models.
✨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 of examples where you've successfully communicated with non-technical team members.
✨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.
