About this role

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.

About Orion

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.

Job overview

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 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 verses 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. “Because we’ve always done it this way” is not a phrase you like to use.
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.

For additional information on BlackRock, please visit @blackrock | Twitter: @blackrock | LinkedIn: www.linkedin.com/company/blackrock

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)