At a Glance
- Tasks: Tackle complex challenges using advanced analytics and AI to drive business impact.
- Company: Join Macquarie Asset Management, a global leader in asset management.
- Benefits: Enjoy 25+ days of leave, wellbeing days, and flexible working arrangements.
- Other info: Diverse and inclusive workplace with excellent career development opportunities.
- Why this job: Make a real difference with cutting-edge AI solutions in a supportive team.
- Qualifications: 4+ years in Data Science, proficient in Python or R, and strong communication skills.
The predicted salary is between 60000 - 80000 ÂŁ per year.
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.
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
- 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.
Benefits
- 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 caregivers
- Paid fertility leave for those undergoing or supporting fertility treatment
- 2 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.
Our commitment to diversity, equity and inclusion
We are committed to providing a working environment that embraces diversity, equity, and inclusion. We encourage people from all backgrounds to apply regardless of their identity, including age, disability, neurodiversity, gender (including gender identity or expression), sexual orientation, marriage or civil partnership, pregnancy, parental status, race (including ethnic or national origin), religion or belief, or socio‑economic background. We welcome further discussions on how you can feel included and belong at Macquarie as you progress through our recruitment process. 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.
Data Scientist employer: Macquarie Group
Contact Detail:
Macquarie Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Macquarie on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Make sure you can confidently discuss your experience with Python, R, and AI techniques. We want to see how you tackle complex challenges!
✨Tip Number 3
Show off your communication skills! Be ready to explain your projects in simple terms. Remember, you’ll be working with diverse stakeholders, so being able to translate tech jargon into business language is key.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Macquarie.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience in Data Science, especially if you've worked in financial institutions. We want to see how your skills in Python or R can tackle the challenges we face at Macquarie!
Tailor Your Application: Don’t just send a generic CV! Tailor your application to reflect how your background aligns with our needs in analytics and AI. We love seeing candidates who understand our mission and can contribute to our data-driven culture.
Communicate Clearly: Your communication skills are key! Be sure to articulate how you can translate complex technical solutions into business-friendly language. We’re all about collaboration, so showing you can connect with diverse stakeholders is a big plus.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Macquarie Group
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python or R, as these are crucial for the role. Brush up on your knowledge of cloud infrastructure and be ready to discuss any experience you have with AI workflows, especially using Anthropic Claude API or Google Gemini API.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex challenges using advanced analytics. Think about how you’ve automated processes or built tools that improved productivity, and be ready to explain your thought process clearly.
✨Communicate Like a Pro
Since you'll need to translate technical jargon into business language, practice explaining your past projects to someone without a technical background. This will help you demonstrate your excellent communication skills during the interview.
✨Emphasise Team Collaboration
Highlight your experience working in agile scrum teams. Be prepared to share examples of how you’ve collaborated with engineers, product owners, and other stakeholders to deliver AI solutions, showcasing your ability to thrive in a multi-disciplinary environment.