Data Science Analyst

The Team

The Data and Machine Learning division at Man Group is dedicated to ensuring the business can generate valuable insights from data. The team owns the sourcing and delivery of traditional and alternative data to our investment teams as well developing and supporting Man Group's central data platform. The team is also responsible for development of generative AI tooling to drive innovation and accelerate business processes.

The function seeks to unlock the value in data by partnering with investment teams to source new and diversifying datasets and build scalable evaluation methods and insights on data. The core value which unifies us is a passion to utilise science, technology, and data to enhance our investment and business processes.

The Role

As an Analyst in the Data Science Analysts team, you will use your specific and general skills to support the quantitative research and portfolio management teams in the development of data driven trading models. Your focus will be on acquiring, cleaning, mapping, and analysing, large structured and unstructured datasets for alpha generation. On some projects you will act as a subject matter expert, delivering high quality exploratory data analysis and insights.

You will have responsibilities ranging from data vendor scoping through to data ingestion, exploratory analysis and prototyping robust data pipelines. The team’s aim is to provide a consistent and scalable approach to data delivery and analysis along with a low touch data management process. This is delivered through a series of small self-managed projects working with the relevant investment teams and other members of the data team.

Responsibilities

• Collaborate with investment teams to identify data opportunities, propose creative use cases, and recommend datasets to inform investment strategies.
• Acquire, transform and analyse large, messy and unstructured datasets to support investment research and decision-making.
• Maintain strong data vendor relationships, evaluate, document and compare new data offerings to assess their applicability to our investment teams.
• Research company KPIs, test relevant datasets and document findings to support investment teams and maintain an accessible knowledge base.
• Contribute to firm-wide data initiatives, enhancing the data ecosystem, and stay informed on industry trends in alternative data.
• Build new proof-of-concept data products to test investment hypotheses and collaborate with technology to productionise them

Requirements

• 2 years’ experience in a related position.
• Ability to present results, conclusions and translate technical concepts to non-technical audiences.
• Entrepreneurial mindset with a willingness to learn investment team requirements and the ability to proactively push new data-driven solutions that solve business questions for them.
• Strong academic record and higher education degree in a STEM field.
• Proven experience in timeseries data analysis, statistical techniques and data visualisation
• Expertise in Python data science stack including Pandas, Numpy, Spark, matplotlib, Jupyter. SQL experience is a plus.
• Experience with ETL and evaluation of large datasets.
• Working knowledge of Snowflake, Linux / UNIX, Git, Jira is preferable.
• Excellent attention to detail.
• Self-organised with the ability to effectively manage time across multiple projects and with competing business demands and priorities.
• Previous experience of working with investment professionals in a fast-paced environment is preferable but not essential.

Working Here

Man Tech has a small company, no-attitude feel. It is flat structured, open, transparent and collaborative, and you will have plenty of opportunity to grow and have enormous impact on what we do. We are actively engaged with the broader technology community.

• We host and sponsor London’s PyData and Machine Learning Meetups. Aeron meetups are also held at Riverbank House.
• We open-source some of our technology including parts of our Data Platform. See https://github.com/man-group
• We regularly talk at leading industry conferences, and tweet about relevant technology and how we’re using it. See @ManQuantTech