Data Scientist (VP)

WhatYou’llbe Doing

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

• Form adeep understanding ofCompany Intelligencecustomers, products, and proprietary datasets toensure solutions are tailored to client needs and market opportunities.

• Explorethird-partydatasetsto understandand advise oncomposition,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 ensuringrobust control, testing, and evaluationmechanisms are in place.

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

• Operate as a “full-stack” Data Scientist– takingprojects from problem formulation to production.

• Exemplify anddemonstratebest-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.

• Determinethe 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 drawactionable 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.

• CollaborateacrossData Science andthe broaderEngineeringdivisiontoset and elevate best practicesand development standardstoincrease 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, andto inspire action.

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

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

Who You Are

• You approachproblems analytically, using evidence and structured thinking todelivereffective data-driven solutions.

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

• Youarecommitted tomeasuring the impact of your workandproactivelydevelop feedback loops to inform continuous improvement.

• Youseektounderstandbusinessobjectivesand customer needs,whilemaintainingthedeeptechnicalexpertiserequired to deliver effective, high-quality solutions.

• Youperform well in a fast-paced environment, developing iterative,sustainable solutions,withlong-term vision, andexemplifyingbest practicese.g.,security, code quality, documentation.

• You have agrowth mindset; youarecurious to discover andexcitedto learnnew technologies, ways of working, and other skills.

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

TechnicalRequirements

• 5+ years’ experienceapplying data science,machine learning, or AIin a commercial setting.

• Track recordof successfully delivering end-to-end data science,machine learning, or AIsolutions.

• Experience leadingtechnicalinitiatives,managing direct reports,mentoring, and developing junior data scientists.

• Intermediate /proficientprogramming skillsin Python & SQL. 

• Proficientuser of core Data Science Python libraries includingPandas, NumPy, scikit-learn, Matplotlib or equivalents.

• Experienceusingrelational databaseand data warehouse technologies to queryforandmanipulate data.

• Proficientknowledge ofsupervised and unsupervised machine learning, andassociatedconcepts such as model selection, feature engineering, hyperparameter tuning, andevaluation metrics.

• Proficient user offrameworks such asPyTorch,XGBoost, scikit-learn, or equivalentsto develop andoptimizemachine learning models.

• Strong data visualisation and storytelling skillsusinge.g.,Metabase,Matplotlib or equivalents.

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

• Track recordof successful collaboration with senior stakeholdersand cross-functional teams.

• Experience withMLOpspracticesincludingmodel deployment, monitoring, lifecycle management,andexperiment trackingusingMLFlowor equivalent.

• Experiencedesigning and architecting scalableandmaintainabledata science and ML systems.

• Experience usingacloud computing platform such as AWS, Azure, GCP or equivalent.

• Secure knowledge of software engineering practicessuch as CI / CDpipelines, containerization(Docker, Kubernetes etc.),collaborative development using Git,testing, andcodequality assessment.

Desirable

• Experiencedevelopingproduction-qualitysolutionsleveraginggenerativeor agentic AI.

• Experience developingscalabledata pipelinesand transforming data using tools such asdbt.

• Experienceleveragingand/ orfine-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 servicessector andalternative assetse.g.,private equity,real estate, and infrastructure.