Role Overview
Head of Data Science & AI spearheads the asset management firm’s data‑driven initiatives, responsible for developing and executing a strategy to harness data and artificial intelligence across the organization. This role oversees advanced analytics, AI model development, and the governance of AI/ML usage. The Head ensures that the firm leverages AI ethically and effectively to gain insights, improve investment research, enhance client experiences, and optimise operations. They establish frameworks for AI innovation, governance, and collaboration, combining deep technical expertise with leadership to transform data into a competitive advantage, while upholding strict standards of accuracy, transparency, and client trust.
Key Responsibilities
- AI Strategy: Define and lead a comprehensive AI strategy, refining it based on emerging technologies and business needs.
- Model Development & AI Innovation: Lead a team in developing predictive models and AI solutions, guiding them through the model development life cycle.
- AI Governance & Ethics: Establish AI governance frameworks, ensuring responsible use, compliance with regulations, and alignment with fiduciary responsibilities.
- Enablement & Collaboration: Foster collaboration between Data Science and other units, integrating AI solutions into business processes.
- Emerging Technology & Thought Leadership: Monitor industry trends, lead innovation initiatives, and advocate for investments in data science capabilities.
Required Qualifications
- Education: Master’s or Ph.D. in Computer Science, Data Science, Statistics, Engineering, or related field.
- Experience: 10+ years in data science or analytics, with at least 5 years in a leadership role, preferably in financial services.
- Technical Proficiency: Deep expertise in machine learning, statistical modelling, and data analysis; hands‑on experience deploying models with large datasets.
- Industry Knowledge: Understanding of asset‑management products, portfolio management, and how data and AI are used in investment management.
- Leadership & Communication: Proven ability to lead data science teams, manage complex projects, and communicate insights to senior executives.
Preferred Experience
- Asset Management Analytics: Experience building investment signal models or automating risk analytics.
- AI Governance Implementation: Experience establishing AI/ML governance processes and ensuring regulatory compliance.
- Advanced Analytics Tools: Familiarity with finance libraries, visualisation tools, and specialised AI contexts.
- Innovation & Research: Published work, patents, or conference presentations in AI or data science related to finance.
Technical Skills
- Programming & ML Tools: Python (pandas, scikit‑learn, TensorFlow/PyTorch), R, SQL, notebooks, Git.
- Machine Learning & AI: Proficiency in regression, classification, clustering, tree‑based models, neural networks, and MLOps practices.
- Data Platforms: Experience with relational and NoSQL databases, big data frameworks, cloud services (AWS, Azure, GCP).
- Analytics & BI: Visualisation tools such as Tableau, Power BI, or Python libraries.
- AI Ethics & Security: Knowledge of bias detection, explainability techniques, and data security best practices.
Soft Skills & Leadership Competencies
- Strategic Vision & Innovation: Craft and communicate a clear AI vision that drives business value.
- Ethical Leadership: Advocate for responsible AI and enforce ethical standards.
- Communication & Storytelling: Explain complex analytics in plain language to non‑technical stakeholders.
- Collaboration & Influence: Partner across IT, investment, compliance, and client teams to embed AI solutions.
- Mentorship & Talent Development: Build and nurture a high‑performing data science team.
- Problem‑Solving & Resilience: Approach data challenges methodically and persistently.
Benefits
- Hybrid working and reasonable accommodations
- Generous holiday policies
- Paid volunteer time
- Professional development support and tuition reimbursement
- Diversity, Equity, and Inclusion initiatives
- Maternal/paternal leave benefits
- Headspace subscription
- Corporate membership to ClassPass and other health benefits
- Unique employee events and programmes
- Complimentary beverages, snacks, and employee happy hours
Compensation and Bonuses
Position may be eligible for an annual discretionary bonus award from the profit pool, based on company, department, team, and individual performance.
Equal Opportunity Statement
Janus Henderson Investors is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. All applications are subject to background checks.
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