Business Development
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The Distribution function is the client facing arm of the Asset Manager, encompassing Sales, Relationship Management (RM), and Client Service, operating in over 30 countries. As the function continues to grow and develop globally, so the need to be smarter about how we make decisions becomes more important.

As a department we are looking to embed data into the centre of everything that we do and develop an ecosystem where sales staff and RMs are able to use data driven insights to help them be effective in their day to day decision making. This ranges from suggesting which clients to speak to and which products to talk about, to identifying actions to help us defend our book of business.


The MI & Analytics team is a business facing team embedded within the Distribution function, located primarily in London, but serving a diverse and global set of consumers at all levels right across Distribution.


Within this area, we are forming a new Distribuiton Data Science team to drive the agenda forward. The team will have responsibility for designing and developing a series scalable tools and widgets to generate and deliver insights into the hands of sales staff and RMs. This encompasses everything from running data science research projects, to developing proof of concepts, building scalable, automated solutions, and integrating these into the day to day lives of users.


Data Science in Schroders


Schroders has a large and established Data Science capability called the Data Insights Unit (DIU), residing primarily in the Investment Division. The new team will have close association with the DIU, and would be expected to share knowledge, tools and techniques.

The DIU’s mission is to bring scientific rigour to all business decisions in Schroders. In essence this is done by:
1. making available new data sources,
2. unlocking the value in data by providing a research service, answering business questions by analysing these datasets,
3. scaling the value in data by building Insight Products: generalising those analyses or anticipating those questions by alerting people to relevant changes before they know to ask.
Throughout all these the DIU are using specialist Data Science tools and techniques including Big Data technologies, Intelligence Augmentation and Artificial Intelligence techniques, and insights from the world of Behavioural Science.

The quantity of information available for investment research purposes is increasing at such a rate that traditional industry practices and skillsets are unable to absorb and process it. Global trends in digitalisation, social media, open data and technology are all creating vast streams of alternative data that are often highly unstructured and obscure. However, they contain valuable and often unique insights. The Data Insights team aims to find these new and potentially unorthodox datasets, extract the rich, hidden information they contain and use their expertise to enhance traditional fundamental research.


Overview of role

This is a new Manager level position, responsible for leading a newly formed and virtual Distribution Data Science. The role will require matrix management of the team comprising three data scientists and three data engineers embedded within the Distribution function.


You will be responsible for leading the team’s activities; helping set the roadmap for embedding data driven decision making in the function; having oversight of all of the data science projects in Distribution; accountability for the successful deployment of tools and widgets; and responsibility for training and developing the team in using the latest tools and techniques.


A key part of this role will be to ensure the team is closely aligned to the DIU and the role holder will be an associate DIU member. The applicant will be expected to participate in data science knowledge sharing, and both contribute to and draw upon the expertise of the broader Schroders community of data professionals.


The applicant will have a strong preference towards working in reproducible data workflow tools such as Jupyter and RMarkdown, but won’t be afraid of interacting with complex Excel/VBA models and other legacy data systems. The applicant will take pleasure from finding simple solutions to complex problems.


Previous experience in the investment industry, or working in a B2B sales function would be valuable, but is not required if the applicant can demonstrate a passion for understanding how businesses and sales functions operate.

This role provides the opportunity to stamp your own mark on a dynamic and growing business function in a role that will be key to the future success of the business.

Key Responsibilities:

Data Insights & Analytics

• Act as a Subject matter expert for Data Science within Distribution
• Set up and run pilot, and proof of concept analytics projects within Distribution, and where successful roll projects out globally
• Oversee the provision of data insights: Identify, prepare, join, and blend various internal and external data sets, and interrogate and analyse the results in order to gain insights currently unavailable to management
• Design and create prototype self service analytical tools and dashboards, ad-hoc analysis reports, and presentations
• Deliver and promote new and existing insight solutions to a broad range of internal customers through traditional and innovative methods.
• Coordinate Data Science projects with other non-investment business areas
• Train up members of the team and wider department on the latest tools and techniques.

Management and team responsibilities

• The role holder will have matrix managerial oversight of two data scientists and three data engineers assembled from other departments based in London forming a feature team of six.
• By managing the overall success of the delivery of the feature team, you will have responsibility for the projects worked on by the data scientists and engineers and be expected to maintain the backlog of projects and oversee delivery of these projects.
• This is a player-manager role where you will be expected to be involved in designing and building solutions as well as overseeing the overall delivery of the team.

Skills / Experience


• Experienced in the development and deployment of analytical data solutions
• Experienced at managing and motivating small teams
• Good interpersonal and communication skills – capable of interacting confidently at all levels of the Distribution organisation including overseas stakeholders
• A team-player, with the ability to operate effectively in a collegiate, collaborative, high performance environment
• ETL / Data Pipelining / Data Engineering skills
• Statistical analysis and interpretation
• Creating clear and effective visual displays of data
• Influencing senior business stakeholders
• Creative thinking
• Commercial focus
• Pragmatic, action-oriented
• Programming experience in R or python.



• R {Tidyverse, Rmarkdown, Shiny}
• Python {numpy, pandas, requests, selenium}
• Linux experience and shell scripting.
• Relevant degree subject (e.g. Statistics, OR, Data Science, any Science)
• Meaningful data modelling experience using SQL-based Data Warehouses
• Big data experience such as Hive.
• Asset Management / Investment practices

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