At Macquarie, you're empowered to shape a career that's rewarding in all the ways that matter most to you. Macquarie employees can access a wide range of benefits which, depending on eligibility criteria, include: 1 wellbeing leave day per year and a minimum of 25 days of annual leave.26 weeks' paid parental leave for primary caregivers along with 12 days of paid transition leave upon return to work and 6 weeks' paid leave for secondary caregiversPaid fertility leave for those undergoing or supporting fertility treatment2 days of paid volunteer leave and donation matching
Access to a wide range of salary sacrificing options
Benefits and initiatives to support your physical, mental and financial wellbeing including, comprehensive medical and life insurance cover
Access to our Employee Assistance Program, a robust behavioural health network with counselling and coaching services
Access to a wide range of learning and development opportunities, including reimbursement for professional membership or subscription
Access to company funded emergency and backup dependent care services
Recognition and service awards
Hybrid and flexible working arrangements, dependent on role
Reimbursement for work from home equipment
About Macquarie Asset Management
Macquarie Asset Management is a leading global asset manager, trusted by institutions, individuals and communities to responsibly manage $A720 billion in assets. MAM provides clients with a diverse range of investment solutions that seek to deliver superior risk-adjusted returns.
All figures as at 31 September 2025, excluding assets acquired by Nomura on 1 December 2025.
Our commitment to diversity, equity and inclusion
Our aim is to provide reasonable adjustments to individuals as required during the recruitment process and in the course of employment. If you require additional assistance, please let us know during the application process.
Additional Information
The Data Science, Analytics and AI group within Macquarie Asset Management aspires to create a data-driven decision-making culture and support business growth by advancing our capabilities in analytics and AI.
At Macquarie, our advantage is bringing together diverse people and empowering them to shape all kinds of possibilities. We are a global financial services group operating in 31 markets and with 56 years of unbroken profitability. You'll be part of a friendly and supportive team where everyone - no matter what role - contributes ideas and drives outcomes.
What role will you play?
You will tackle complex challenges using advanced analytics and agentic AI.
Leveraging state of the art AI techniques, you will deliver transformative business impact across our private market investment divisions, including Real Assets, Real Estate, and Credit and Insurance.
Example challenges include automating data extraction from unstructured investment documents, building AI agents to streamline portfolio company analysis, creating intelligent systems to support deal screening workflows, and developing tools that augment analyst productivity across asset classes.
What you offer
4+ years' experience in Data Science, working for a financial institution and ideally supporting across one or more private asset classes
Highly proficient in Python or R, a deep understanding of cloud infrastructure, and hands-on experience building and deploying agentic AI workflows
Experience with Anthropic Claude API or Google Gemini API strongly preferred and familiarity with Atlassian tools and scrum methodology is advantageous
Excellent communication skills, able to translate business requirements into technical solutions and clearly articulate ML and AI approaches to a diverse range of stakeholders
Able to thrive within a collaborative, multi-disciplinary, cross-functional agile scrum team, working alongside engineers, product owners and business stakeholders to deliver complex AI solutions
We love hearing from anyone inspired to build a better future with us, if you're excited about the role or working at Macquarie we encourage you to apply.
Efinancialcareers · London, UK