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- Tasks: Join our team to drive data analysis and machine learning in Private Equity.
- Company: We are a leading firm in the Private Equity space, focused on innovative data solutions.
- Benefits: Enjoy a competitive salary, bonuses, and a hybrid work model with 4 days in the office.
- Why this job: Be part of a dynamic investment team and make impactful decisions with data.
- Qualifications: Must have experience in Private Equity or strategy consultancy, with strong Python and SQL skills.
- Other info: This role does not offer sponsorship; apply if you meet the qualifications!
The predicted salary is between 90000 - 210000 £ per year.
Preferable: 6+ YOE Salary Range: £75,000-90,000 depending on experience Smart Spaces is an award-winning, industry-leading white-label IoT platform, providing an all-in-one solution for building management systems control and communication. Our platform smart-enables workplaces, adding efficiency to daily work life for occupiers, employees, property owners, and managers. Our IoT application helps manage everything in your building, from granting access, system controls, and energy efficiency reports, to room booking and maintenance queries. This role is a great opportunity for a data-driven leader to get involved with all aspects of managing our data, from engineering to analytics to AI product development. Lead an agile Data Science & Analytics team to spearhead the company\’s data & AI strategy Develop & own the Data & AI product roadmap – by researching, prototyping, and implementing solutions to business challenges, from concept to production Design & implement ETL data pipelines to serve data for reporting & analytics, transforming sensor & operational data & calculating business metrics Create interactive dashboards & visualisations to provide insights from our broad datasets, including data such as building occupancy, energy, & air quality Work with customers to understand their data & reporting requirements, effectively communicate these to stakeholders, and develop product solutions Programming: Proficient in at least one language with a strong knowledge of OOP concepts (Python or C# preferred) Data Engineering: Experience designing and implementing ETL pipelines, transforming & cleaning data Data & API\’s: Strong experience working with databases & API\’s, with experience guiding data architecture decisions Data Visualization & Reporting: Experience with BI tools beneficial Management : Self-motivated with good project management skills to manage your own time & that of your team within an Agile/Sprint framework AI Development: Knowledge of AI tools and AI application development, keen interest to learn more Digital Twin / Simulation experience Hybrid role with three days in-office expectation Private health insurance Company pension scheme Discounts and Offers Platform
Data Science Data Science Data Scientist (Remote) employer: Smart Spaces®
Contact Detail:
Smart Spaces® Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Data Science Data Scientist (Remote)
✨Tip Number 1
Make sure to highlight your experience in Private Equity or strategy consultancy during your conversations. This is crucial as it directly aligns with the role's requirements and will help you stand out.
✨Tip Number 2
Familiarize yourself with the latest trends in Machine Learning and Data Visualization tools like Tableau and Power BI. Being able to discuss recent projects or innovations in these areas can impress the hiring team.
✨Tip Number 3
Prepare to discuss specific examples of how you've used Python and SQL in past projects. Concrete examples will demonstrate your technical skills and show that you're ready to contribute from day one.
✨Tip Number 4
Engage with the investment community on platforms like LinkedIn. Networking with professionals in Private Equity can provide insights and potentially lead to referrals, increasing your chances of landing the job.
We think you need these skills to ace Data Science Data Science Data Scientist (Remote)
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your experience in Private Equity or strategy consultancy. Clearly outline any projects you've worked on that relate to data science in these fields.
Showcase Technical Skills: Detail your proficiency in Python, SQL, and data visualization tools like Tableau or Power BI. Provide specific examples of how you've used these skills in previous roles.
Tailor Your CV: Customize your CV to align with the job description. Use keywords from the listing, such as 'due diligence', 'machine learning', and 'cashflow predictive models' to catch the recruiter's attention.
Craft a Strong Cover Letter: Write a compelling cover letter that explains why you're interested in this role and how your background makes you a perfect fit. Mention your understanding of the private equity space and your passion for data science.
How to prepare for a job interview at Smart Spaces®
✨Showcase Your Private Equity Experience
Make sure to highlight your experience in Private Equity during the interview. Discuss specific projects you've worked on, especially those involving data analysis or strategy consultancy, as this will demonstrate your relevance to the role.
✨Demonstrate Technical Proficiency
Be prepared to discuss your experience with Python and SQL in detail. You might be asked to solve a problem or explain how you've used these tools in past projects, so brush up on your technical skills and be ready to provide examples.
✨Prepare for Data Visualization Questions
Since the role involves driving data visualization with Tableau or Power BI, familiarize yourself with common use cases and best practices. Be ready to discuss how you've used these tools to present data effectively to stakeholders.
✨Engage with Senior Stakeholders
As you'll be part of the front office investment team, it's crucial to show that you can communicate effectively with senior stakeholders. Prepare examples of how you've successfully collaborated with senior team members in previous roles.
