Head of Data Value Labs

Hargreaves Lansdown

Head of Data Value Labs driving data strategy for Hargreaves Lansdown. Transforming data into operational asset and delivering insights for business growth.

Posted 6/18/2026full-timeBristol • 🇬🇧 United KingdomLeadWebsite

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPythonSQLTableau

About the role

Key responsibilities & impact

Direct the full lifecycle of data science projects, from ideation and hypothesis testing to model development, deployment, and ongoing performance monitoring / compliance adherence, across the following model types:
Propensity Models: To identify clients most likely to invest further, take up new products, or be at risk of churn, with ongoing feedback loops to ensure that the outputs are utilised and optimised over time.
Next Best Action (NBA): To guide client interactions, campaigns and outcomes, including supporting targeted support (where relevant).
AI & Machine Learning: Champion the ethical and effective use of Gen-AI, AI and ML to improve model performance, automate processes and drive incremental insights.
Develop the client Insights, nudges & alerts strategy with business input and ensuring alignment with CRM, targeted support, Martech and Digital team activities.
Synthesise data from multiple sources (transactional, behavioural, demographic) to build a 360-degree view of the client, understanding their needs, goals, and behaviours.
Design, develop, and implement a system of automated, personalised and prioritised client insights, nudges and alerts to:
Encourage positive financial behaviours (e.g., utilising tax allowances, diversifying portfolios, avoiding detrimental trading)
Highlight relevant opportunities (e.g., IPOs, regulatory changes, new product launches, market updates)
Proactively address potential issues (e.g., large cash balances, portfolio imbalances)
Guide clients towards app and online functionality to help them with their needs.
Across these, the Head of Data Value labs will work with the CRM team to assess how to deliver personalisation at scale to integrate these insights, nudges and alerts into the client journey across all digital touchpoints (app, web, email) to create a truly personalised and relevant experience.
Collaborate with the business to unlock processes through data and the capabilities of the broader data marketplace.
Champion efficiencies and develop repeatable delivery models to drive out manual processes, reporting and calculations to reduce costs and operational risks, working with Risk colleagues to ensure that development is in line with policy and regulatory requirements.
Build a High-Performing Team: Recruit, mentor, and lead a world-class team of analytics professionals, fostering a culture of curiosity, innovation, and commercial focus.
Define and align the roadmap: Develop and own the strategic roadmap for analytics, ensuring it is aligned with the company's overarching commercial goals.
Champion Data Culture: Be an advocate for data-driven decision-making across the organisation, effectively communicating the value and potential of analytics to all stakeholders.
Stakeholder Management: Build strong, collaborative relationships with key stakeholders across the business, including the Executive team, Marketing, Product, Technology, and Finance.

Requirements

What you’ll need

Proven experience - Senior analytics leadership role, ideally within D2C financial services, wealth management, banking, fintech, or a similar regulated industry.
Strategic Thinker - Ability to develop long-term commercial strategies aligned with company goals.
Proficiency in market analysis and competitive positioning, with expertise in translating data into strategic insights for a senior executive audience.
Technical Skills - Deep understanding of statistical analysis, machine learning techniques, and experimental design (A/B testing).
High proficiency with data science programming languages (e.g., Python, R) and data manipulation (SQL).
Experience with modern data visualisation and BI tools (e.g., Sigma, Tableau, Power BI).
Familiarity with cloud-based data warehousing and analytics platforms (e.g., AWS, Azure, GCP, Cloudera, Snowflake, Teradata).
Data Science and Gen AI – Strong leadership skills in data science and Gen AI, including guardrails definition, colleague training, technology platform and use case assessment and prioritisation, model monitoring, feature engineering and optimisation.
Track record of developing and deploying predictive models and AI/ML solutions that have driven tangible commercial value that is recognised by the business and clients.
Client centric experience, performance and behavioural analytics – ability to shape a broader data driven strategy for client nudges, insights and alerts with clarity around orchestration, feedback mechanisms (to improve performance), consent management and coordination with adjacent workstreams. Including how batch, semi real-time and real-time data feeds will all drive important content, albeit at different velocities.
Financial Acumen - Understanding of financial principles, budgeting, and forecasting.
Ability to manage profit and loss statements effectively and produce accurate forecasts based on behaviours.
Leadership and Team Management - Experience in leading cross-functional teams and fostering collaboration.
Skills in mentoring and developing talent within the Commercial Performance team.
E2E commercial expertise of Wealth and broader financial products, including features, revenue levers, cost drivers.
Understanding of Open Finance data – knowledge of API framework, consent / revalidation requirements, data latency, transactional categorisation and typical data features to drive broader insights for clients at HL.
Awareness of future roadmap for Open Finance data with active engagement with 3rd-party suppliers to review future use cases.
Understanding of Open Data – ability to assess potential 3rd-party data opportunities to enhance understanding and client experience, including working with the broader business to produce accurate business cases.
Customer-Centric Approach - Focus on understanding customer needs and preferences that will drive commercial upside.
Communication Skills - Strong verbal/ written communication skills to convey strategies and insights clearly to colleagues, ExCo and Board.
Collaborative Approach – knows how to build deep and trusted relationships with senior leaders to deliver joined up programmes that add value (revenue. Costs, risk) to the business.
Project Management - Skilled in detailed work planning and providing input and tracking for multiple projects simultaneously to drive upside.
Technological Proficiency - Understanding of CRM systems and other commercial performance tools.

Benefits

Comp & perks

Discretionary annual bonus * and annual pay review
25 days * holiday plus bank holidays and 1-day additional Christmas closure
Option to purchase an additional 5 days holiday **
Flexible working options available, including hybrid working
Enhanced parental leave
Pension scheme up to 11% employer contribution
Income Protection and Life insurance (4 x salary core level of cover)
Private medical insurance*
Health care cash plans - including optical, dental, and out patient care
Health screening programme
Help@hand - confidential support including mental health counselling and remote GP
Wellhub - unlimited access to fitness provider s and wellness coach sessions
Variety of travel to work schemes with bike storage and shower facilities
Inhouse barista and deli serving subsidised coffee and sandwiches
Two paid volunteering days per year * dependant on role level ** only available to select during our annual benefits window, in November each year

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data sciencemachine learningstatistical analysisA/B testingPythonRSQLpredictive modelingfinancial analysisdata visualization

Soft Skills

strategic thinkingleadershipteam managementcommunicationcollaborationcustomer-centric approachmentoringstakeholder managementproject managementinnovation