Data Scientist (VP)

Data Scientist (VP)

London Full-Time 72000 - 108000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Join our team to revolutionise data collection and implement cutting-edge AI/ML solutions.
  • Company: Be part of Preqin, a dynamic division of BlackRock, transforming private markets data globally.
  • Benefits: Enjoy flexible time off, education reimbursement, and comprehensive health resources.
  • Why this job: Make a real impact in a fast-paced environment while collaborating with innovative minds.
  • Qualifications: 7+ years in data science/ML; strong programming skills, preferably in Python.
  • Other info: Hybrid work model with at least 4 days in the office, fostering collaboration and learning.

The predicted salary is between 72000 - 108000 £ per year.

This role sits within Preqin, a part of BlackRock. Preqin plays a key role in how we are revolutionizing private markets data and technology for clients globally, complementing our existing Aladdin technology platform to deliver investment solutions for the whole portfolio.

The Orion project transforms the core of Preqin by changing the way we collect data. The team moves fast and independently, while also contributing to setting best practices across teams. We combine automation with Machine Learning and AI and with advanced data and engineering solutions.

At Preqin, data is at the heart of everything we do. We operate a world-class data research team and provide alternative asset data highly prized by thousands of customers worldwide. Preqin engineering is evolving into a fast-paced and autonomous culture; our Data Scientists have an opportunity to significantly accelerate these changes and help shape our organisation for the future.

Working in the platform team, you will be responsible for the technical excellence of our platform services, shaping, collaborating, and creating new and changing existing implementations as necessary to raise the bar technically and improve the way we manage our services. In platform, we own some of the business-critical services such as authentication as well as a series of new work streams focused on user management, data management and architectural oversight. You will also work with technical teams across the business supporting them to build, and implementing yourself, a variety of technological solutions.

The platform team is critical to the success of Preqin's technology strategy providing the foundations for cross-team services and enablement for teams located in other business units. The team has recently adopted this direction and there is tremendous opportunity to impact the way we do technology at Preqin and helping to contribute to Preqin's mission to unleash the power of data, increasing transparency in alternative assets and empowering the finance community to make better decisions across the global alternatives market.

What you'll be doing:

  • Accelerate data collection at scale from millions of sources.
  • Design, build, and deploy workflows at scale that seamlessly combine AI/ML with human expertise.
  • Elevate development standards and empower others to adopt them through re-usable services, frameworks, templates, and knowledge sharing.
  • Collaborate with engineering teams across the business to improve time to value and to ensure that the best options for internal technical solutions are known.
  • Explore new technologies, approaches, and ideas that help to drive our business goals in unexpected ways.
  • Understand and translate business problems into data science / machine learning solutions.
  • Align desired business outcomes with clear and observable success measures.
  • Determine the value proposition of data science / machine learning solutions versus alternatives.
  • Propose smart, pragmatic, and diverse approaches to address a variety of business problems.
  • Lead individual and group projects, driving them towards the desired outcome.
  • Forge constructive business relationships with key stakeholders.
  • Prioritise and refine own work and tasks relating to the projects you lead and contribute to.
  • Operate as a "full-stack" Data Scientist - taking projects from problem formulation to production.
  • Design and run focused experiments targeting specific business outcomes.
  • Write quality code to realise models, perform analytics, and draw actionable insights from data.
  • Leverage software development tools and platforms to enable and support solutions.
  • Exemplify and demonstrate best-practice data science and machine learning across the business.
  • Present results and recommendations clearly, succinctly, and honestly to a variety of audiences.
  • Use compelling storytelling to contextualise data visualisations / insights and inspire action.
  • Contribute to the continuous improvement mindset in Data Science and Preqin's wider Technology division e.g., by sharing knowledge and feedback, being a sounding board to colleagues.
  • Stay abreast of the latest developments in data science and machine learning and identify those with business impact.

Who are you:

  • A "let's do it" and "challenge accepted" attitude when faced with the less known or challenging tasks.
  • Ability to perform well in a fast-paced environment, developing iterative sustainable solutions with best practices (security, code quality, documentation) and long-term vision.
  • Curiosity and willingness to learn about new technologies, ways of working and acquire new skills possessing a growth mindset.
  • Understanding that generating positive outcomes requires knowledge of the stakeholder and the problem space to allow effective use of your technical knowledge ability.
  • Passion to improve the capacity of engineering teams to deliver value through collaboration, excellent tooling, and thin configurable services.
  • Excitement to collaborate with technical and non-technical colleagues across teams.
  • Qualifications are not as essential as experience. If you feel you have work examples and projects that illustrate what we need, we're happy to have a conversation.

Technical requirements:

  • Bachelor's degree or higher degree in statistics, data science, computer science, economics, or another quantitative field.
  • 7+ years' experience applying data science / machine learning in a commercial setting.
  • Track record of successfully delivering end-to-end data science / machine learning solutions.
  • Ability to work effectively with senior stakeholders and clients.
  • Excellent communication skills to bridge technology and business.
  • Proficient / intermediate level programming skills, preferably Python.
  • Software collaboration experience using version control, preferably Git.
  • Experience using foundational data science libraries e.g., Pandas, NumPy, scikit-learn or equivalent.
  • Experience applying state-of-the-art machine learning to commercial problems.
  • Experience using software development / deployment tools, platforms, and best practices e.g., CI/CD pipelines, containerization technology and cloud computing platforms.
  • Experience querying for and manipulating data using database technologies.
  • Highly motivated, collaborative, innovative, inquisitive, customer-centric and demonstrates a growth mindset.

Our benefits:

To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.

Our hybrid work model:

BlackRock's hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person - aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.

About BlackRock:

At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children's educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.

This mission would not be possible without our smartest investment - the one we make in our employees. It's why we're dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.

BlackRock is proud to be an Equal Opportunity Employer. We evaluate qualified applicants without regard to age, disability, race, religion, sex, sexual orientation and other protected characteristics at law.

Data Scientist (VP) employer: BlackRock, Inc.

At Preqin, a part of BlackRock, we pride ourselves on fostering a dynamic and innovative work culture that empowers our Data Scientists to drive meaningful change in the private markets data landscape. With a strong emphasis on collaboration, continuous learning, and employee well-being, we offer comprehensive benefits including flexible time off, education reimbursement, and robust support for physical and emotional health. Our hybrid work model not only enhances your professional growth but also ensures you are part of a vibrant community dedicated to transforming the finance industry.
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Contact Detail:

BlackRock, Inc. Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Scientist (VP)

✨Tip Number 1

Familiarise yourself with the latest trends in data science and machine learning, especially those relevant to financial services. Being able to discuss recent advancements or case studies during your interview can demonstrate your passion and knowledge in the field.

✨Tip Number 2

Network with current employees at Preqin or BlackRock through platforms like LinkedIn. Engaging in conversations about their experiences can provide you with valuable insights into the company culture and expectations, which you can leverage during your application process.

✨Tip Number 3

Prepare to showcase your problem-solving skills by thinking of specific examples where you've successfully implemented data science solutions in a commercial setting. Be ready to discuss the impact of your work on business outcomes, as this aligns with the role's focus on delivering value.

✨Tip Number 4

Demonstrate your collaborative spirit by highlighting past experiences where you've worked cross-functionally with technical and non-technical teams. This will resonate well with the role's emphasis on collaboration and communication across various business units.

We think you need these skills to ace Data Scientist (VP)

Data Science
Machine Learning
Statistical Analysis
Python Programming
Data Manipulation
Version Control (Git)
Cloud Computing
CI/CD Pipelines
Data Visualisation
Stakeholder Engagement
Problem-Solving
Collaboration Skills
Agile Methodologies
Technical Communication
Experiment Design

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in data science and machine learning. Focus on projects that demonstrate your ability to deliver end-to-end solutions, especially those that align with the responsibilities outlined in the job description.

Craft a Compelling Cover Letter: Use your cover letter to tell a story about your passion for data science and how it relates to Preqin's mission. Mention specific projects or experiences that showcase your skills in AI/ML and your ability to collaborate across teams.

Showcase Technical Skills: In your application, clearly list your technical skills, particularly in programming languages like Python and tools such as Git. Highlight your experience with foundational data science libraries and any relevant software development practices.

Demonstrate Communication Skills: Since the role requires excellent communication skills, include examples of how you've effectively communicated complex technical concepts to non-technical stakeholders. This could be through presentations, reports, or collaborative projects.

How to prepare for a job interview at BlackRock, Inc.

✨Showcase Your Technical Expertise

As a Data Scientist, it's crucial to demonstrate your technical skills during the interview. Be prepared to discuss your experience with machine learning algorithms, data manipulation using libraries like Pandas and NumPy, and any relevant projects you've completed. Highlight specific examples where you've successfully implemented data science solutions in a commercial setting.

✨Communicate Clearly and Effectively

Excellent communication is key, especially when bridging the gap between technical and non-technical stakeholders. Practice explaining complex concepts in simple terms and be ready to present your past work in a way that showcases its business impact. Use storytelling techniques to make your data insights compelling.

✨Demonstrate a Growth Mindset

Preqin values curiosity and a willingness to learn. During the interview, share instances where you've embraced new technologies or methodologies. Discuss how you've adapted to challenges and what you've learned from them. This will show your potential to thrive in a fast-paced environment.

✨Prepare for Scenario-Based Questions

Expect scenario-based questions that assess your problem-solving abilities. Be ready to discuss how you would approach specific business problems using data science and machine learning. Think about how you can align your solutions with desired business outcomes and articulate your thought process clearly.

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