At a Glance
- Tasks: Join our Portfolio Analytics team to analyse data and develop actionable insights.
- Company: Man Group plc is a leading investment firm with a collaborative culture and innovative approach.
- Benefits: Enjoy competitive pay, generous holidays, wellness amenities, and opportunities for continuous learning.
- Why this job: Make a real impact in finance while working in a dynamic, open-plan office overlooking the Thames.
- Qualifications: Strong programming skills in Python and a degree in a quantitative field are essential.
- Other info: Engage with the academic community and participate in exciting projects across the firm.
The predicted salary is between 43200 - 72000 £ per year.
Job Description
About Man AHL:
Man AHL is one of the world’s longest running diversified systematic investment managers, trading in over 800 markets globally and offering a range of absolute return and long-only quantitative strategies that invest across traditional and alternative markets.
With over three decades of quantitative investment experience, Man AHL is committed to constant innovation and evolution of research. It applies advanced technology and scientific rigour to every stage of the investment process, from data curation and cleaning through to signal generation, risk management and execution. It views risk management and trading and execution as central to alpha generation, and its strategies are designed to understand risk, take appropriate exposures and, where necessary, dynamically adjust exposure.
Man AHL brings together scientists, academics, technologists and finance practitioners who are driven by curiosity, intellectual honesty and a passion for solving the complex problems presented by financial markets. It works closely with the Oxford-Man Institute of Quantitative Finance (OMI), Man Group’s unique collaboration with the University of Oxford, and leverages insights from its field-leading academic research into machine learning and data analytics.
Further information can be found at .
The Team:
AHL Portfolio Management is the team responsible for the portfolio construction and investment management of the firm’s flagship fund. The team has been running for several years. It manages a diverse set of funds both in terms of trading styles and asset classes. It is also responsible for portfolio construction as well as allocation research inside AHL.
The Portfolio Management area is split into two sub teams: Analytics and Monetisation. The Portfolio Analytics team’s purpose is to deliver quantifiable, transparent, and actionable insights into our research process.
The Portfolio Monetisation team’s purpose is to maximise the dollar output of our research in our funds.
Portfolio Analytics:
As part of its mandate, the Portfolio Analytics team is ultimately responsible for delivering transformative actionable insights on the entire estate pipeline, from signal to fund level information. We are an integral part of the decision-making process within AHL for where resources and research efforts are allocated, and our work is a fundamental node in the feedback loop of Portfolio Management and AHL processes.
Team members of Portfolio Analytics team need to be technically strong, write good code rapidly, have strong attention to detail, an aptitude for understanding the internal workings of systems and processes, and a natural talent for uncovering insights.
The ideal candidate will be involved in several areas:
- Working with and analysing a vast amount of data
- Developing analytics, KPIs, metrics
- Carrying out research on transforming data to intelligence
- Writing code, extracting insights and building reporting mechanisms
- Rapidly building extensive knowledge of the AHL estate and leveraging this effectively to generate cross-functional insights and synergies
Technology and Business Skills:
Essential:
- Expertise in a high-level programming language, ideally Python
- Exceptional analytical skills; recognised by your peers as an expert in your domain
- A deep understanding of statistics and an ability to apply to real world problems
- Proficiency with NumPy/SciPy/Pandas or similar
- Ease of handling large data sets
- Understanding risk management techniques and portfolio risk modelling
Advantageous:
- Experience with analysing/managing complex risk
- Either Portfolio Management, systematic Trading, QIS, Financial Engineering experience
- Linux, SQL/Oracle, KDB+
- Experience with machine learning libraries such as sklearn
Personal Attributes:
- Strong academic record and a degree with high mathematical, statistical and computing content e.g. Mathematics, Computer Science, Engineering, Economics or Physics from a leading university
- Exhibiting meticulous attention to detail
- Keen interest or experience in Financial Markets
- Hands-on attitude; willing to get involved with technology and projects across the firm
- Intellectually robust with a keenly analytic approach to problem solving and a positive attitude
- Self-organised with the ability to effectively manage time across multiple projects and with competing business demands and priorities
- Strong interpersonal skills; able to establish and maintain a close working relationship with quantitative researchers, technologists, traders and senior businesspeople alike
- Confident communicator; able to argue a point concisely and deal positively with conflicting views
Working Here:
AHL fosters a performance driven culture, akin to a small company, no-attitude feel. It is flat structured, open, transparent, and collaborative, offering ample opportunity to grow and have enormous impact on what we do. We are actively engaged with the broader research and academic community, as well as renowned industry contributors.
We’re fortunate enough to have a fantastic open-plan office overlooking the River Thames and continually strive to make our environment a great place in which to work.
- We have annual away days and research off-sites for the whole team
- As well as PCs and Macs in our office, you’ll also find numerous amenities such as a Wellness room featuring Peloton bikes, a music room with notably a piano and guitar and a Maker space with light cubes and 3D printer
- We host and sponsor London’s PyData and Machine Learning Meetups
- Man Group has proudly partnered with King’s College London Mathematics School for many years, which offers employees the opportunity to supervise a group of students on a scientific research project or internship
- We open-source some of our technology. See
- We regularly talk at leading industry conferences, and tweet about relevant technology and how we’re using it. See and
Quantitative Researcher - PM Analytics - Man Group plc employer: Man Group plc
Contact Detail:
Man Group plc Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher - PM Analytics - Man Group plc
✨Tip Number 1
Familiarise yourself with the latest trends in quantitative research and portfolio management. Understanding the current landscape will help you engage in meaningful conversations during interviews and demonstrate your passion for the field.
✨Tip Number 2
Network with professionals in the industry, especially those working at Man Group or similar firms. Attend relevant meetups or conferences, such as PyData or Machine Learning events, to make connections and learn more about the company culture.
✨Tip Number 3
Brush up on your programming skills, particularly in Python, and get comfortable with libraries like NumPy, SciPy, and Pandas. Being able to demonstrate your coding abilities in practical scenarios can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your analytical approach to problem-solving. Be ready to share examples of how you've tackled complex data challenges in the past, as this will showcase your expertise and fit for the Portfolio Analytics team.
We think you need these skills to ace Quantitative Researcher - PM Analytics - Man Group plc
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the requirements of the Quantitative Researcher position. Emphasise your expertise in programming languages, particularly Python, and any experience you have with data analysis and portfolio management.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background in mathematics, statistics, or computer science makes you a suitable candidate. Mention specific projects or experiences that demonstrate your analytical skills and attention to detail.
Showcase Technical Skills: Be sure to include any technical skills that are relevant to the role, such as proficiency in NumPy, SciPy, or machine learning libraries. If you have experience with SQL or handling large datasets, highlight these as well, as they are advantageous for the position.
Demonstrate Problem-Solving Ability: Use examples from your past experiences to illustrate your problem-solving skills. Describe situations where you successfully analysed data to derive insights or made decisions based on statistical analysis. This will show your potential employer that you can contribute effectively to their team.
How to prepare for a job interview at Man Group plc
✨Showcase Your Technical Skills
Make sure to highlight your expertise in high-level programming languages, especially Python. Be prepared to discuss specific projects where you've used libraries like NumPy, SciPy, or Pandas to analyse large data sets.
✨Demonstrate Analytical Thinking
During the interview, be ready to solve real-world problems using statistical methods. You might be asked to explain how you would apply your analytical skills to portfolio risk modelling or data transformation.
✨Communicate Clearly and Confidently
As a Quantitative Researcher, you'll need to convey complex ideas succinctly. Practice articulating your thoughts on quantitative research and be prepared to defend your viewpoints while remaining open to feedback.
✨Express Your Interest in Financial Markets
Show your enthusiasm for financial markets and how they intersect with technology. Discuss any relevant experiences or insights you've gained, as this will demonstrate your passion and fit for the role within the Portfolio Analytics team.