Data Scientist (VP)

• Develop data science, machine learning, and AI components for automated data ingestion and enrichment pipelines, and rigorous data verification and maintenance processes.

• Form a deep understanding of Company Intelligence customers, products, and proprietary datasets to ensure solutions are tailored to client needs and market opportunities.

• Explore third-party datasets to understand and advise on composition, structure, quality, and provenance, with respect to the needs of Company Intelligence customers.

• Leverage generative and agentic AI to automate complex workflows and enable autonomous decision making, while ensuring robust control, testing, and evaluation mechanisms are in place.

• Forge constructive business relationships with key stakeholders in Company Intelligence and elsewhere across Preqin & BlackRock.

• Operate as a "full-stack" Data Scientist - taking projects from problem formulation to production.

• Exemplify and demonstrate best-practice data science across Preqin & BlackRock.

• Understand and translate business problems into data science, ML, and AI solutions.

• Propose smart, pragmatic, and diverse approaches to address a variety of business problems.

• Determine the value proposition of data science, ML, and AI solutions vs. alternatives.

• Design and run focused experiments targeting specific business outcomes.

• Lead individual and group projects, driving them towards the desired outcome.

• 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.

• Prioritise and refine your work and tasks relating to the projects you lead and contribute to.

• Collaborate across Data Science and the broader Engineering division to set and elevate best practices and development standards to increase robustness and reduce time to value.

• Present results clearly, succinctly, and transparently to a variety of audiences.

• Use compelling storytelling to contextualize data visualisation and insights, and to inspire action.

• Embrace a mindset of continuous improvement within Data Science and the broader Engineering division by sharing knowledge, providing feedback, and supporting colleagues.

• Stay up to date with the latest developments in data science, machine learning & AI, and identify those with business impact.

• You approach problems analytically, using evidence and structured thinking to deliver effective data-driven solutions.

• You take ownership of your work, hold yourself accountable, and are proactive in driving initiatives through to completion.

• You are committed to measuring the impact of your work and proactively develop feedback loops to inform continuous improvement.

• You seek to understand business objectives and customer needs, while maintaining the deep technical expertise required to deliver effective, high-quality solutions.

• You perform well in a fast-paced environment, developing iterative, sustainable solutions, with long-term vision, and exemplifying best practices e.g., security, code quality, documentation.

• You have a growth mindset; you are curious to discover and excited to learn new technologies, ways of working, and other skills.

• You are keen to collaborate with technical and non-technical colleagues across Preqin & BlackRock, and with customers.

Technical Requirements

Essential

• 5+ years' experience applying data science, machine learning, or AI in a commercial setting.

• Track record of successfully delivering end-to-end data science, machine learning, or AI solutions.

• Experience leading technical initiatives, managing direct reports, mentoring, and developing junior data scientists.

• Intermediate / proficient programming skills in Python & SQL.

• Proficient user of core Data Science Python libraries including Pandas, NumPy, scikit-learn, Matplotlib or equivalents.

• Experience using relational database and data warehouse technologies to query for and manipulate data.

• Proficient knowledge of supervised and unsupervised machine learning, and associated concepts such as model selection, feature engineering, hyperparameter tuning, and evaluation metrics.

• Proficient user of frameworks such as PyTorch, XGBoost, scikit-learn, or equivalents to develop and optimize machine learning models.

• Strong data visualisation and storytelling skills using e.g., Metabase, Matplotlib or equivalents.

• Excellent communication skills to bridge between customers, the business, and technology.

• Track record of successful collaboration with senior stakeholders and cross-functional teams.

• Experience with MLOps practices including model deployment, monitoring, lifecycle management, and experiment tracking using MLFlow or equivalent.

• Experience designing and architecting scalable and maintainable data science and ML systems.

• Experience using a cloud computing platform such as AWS, Azure, GCP or equivalent.

• Secure knowledge of software engineering practices such as CI / CD pipelines, containerization (Docker, Kubernetes etc.), collaborative development using Git, testing, and code quality assessment.

Desirable

• Experience developing production-quality solutions leveraging generative or agentic AI.

• Experience developing scalable data pipelines and transforming data using tools such as dbt.

• Experience leveraging and / or fine-tuning pre-trained models such as BERT.

• Awareness of data ethics, responsible AI, and data governance (e.g. privacy, bias mitigation, compliance).

• Working knowledge of the financial services sector and alternative assets e.g., private equity, real estate, and infrastructure.

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.

This role sits within Preqin, a part of BlackRock. Preqin plays a key role in how we are revolutionising private markets data and technology for clients globally, complementing our existing Aladdin technology platform to deliver investment solutions for the whole portfolio. Company Intelligence is Preqin, a part of BlackRock's, complete solution for investing in private companies. Company Intelligence empowers deal investment teams with granular private company data and deal information to support deal sourcing, initial due diligence, benchmarking, and market-level insights linking assets, funds, managers, and performance data. The multidisciplinary team comprising of Product, Data Scientists, Data Engineers, Software Developers, and BI Analysts work collaboratively to curate and derive rich, auditable private company data sets including firmographics, financials, ownership structures, and deal history. We are on a mission to greatly expand our universe of private companies, data, and signals to further meet client needs around deal sourcing., 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.