Salary £22k-£30k

We’re in need of an Analyst to join our growing team. The work will require a combination of basic analytical methods as well as more advanced data science techniques. The role is to provide analysis and insight solutions for a range of clients. The successful candidate will have a responsibility to ensure that work is delivered on time, within scope and provide value for our clients. They’ll have a love of problem solving, data storytelling and be comfortable working collaboratively. They should have confidence to build relationships with both internal teams and external customers and the ability to communicate effectively with both technical and non-technical audiences.

This is an opportunity to carve out a role within a successful, growing company. If you’ve the qualities we’re looking for, we’ll do our best to create the right-shaped space in which you can flourish. You could be fresh out of university or you might have a couple of years’ experience under your belt. As important as your direct experience is your commitment, your ability to interpret the data and requirements in front of you, and the insight and outcomes that you’re able to communicate to your co-workers and Wood for Trees clients.

The Analyst will work within the analysis team and wider organisation to deliver internal and external insight projects.

Role responsibilities

  • Conduct data analysis across a range of clients
  • Interrogate and present analysis from large SQL databases
  • Work with senior analysts to ensure appropriate analysis is delivered in a robust and timely basis to answer client requirements
  • Interpret analytical output and develop recommendations to feed back to our clients

Experience/person specification 

Required

  • Strong communication and teamwork skills
  • Good understanding of data, preferably with some experience of a high-level analytical background and excellent numerical skills
  • Understanding of database structures and ability to manipulate large datasets
  • Ability to manipulate and present data within software applications, such as Excel
  • Excellent planning and time management skills
  • Methodical, pragmatic, questioning mind
  • Clear, concise communication skills at a level appropriate for the audience
  • Positive and flexible attitude and ability to work well in a small team

Beneficial

  • Experience of working with (or in) a charity or not-for-profit organisation and external suppliers
  • Experience of SQL for querying databases and extracting datasets
  • Use of R, Python or a similar statistical software suite

Benefits

  • Flexible, home working (commutable distance to Bath preferred)
  • 33 days holiday (including Bank Holidays) plus 3 volunteering days
  • 3% employer contributory pension
  • Birthday meal on us
  • Cycle to work scheme and repairs
  • Health and wellbeing benefits
  • Retail discounts
  • Regular social events
  • Access to a range of further benefits through Inc & Co – Club 100. For the complete list, visit club100.incandco.com 

About Wood for Trees

Established over 10 years ago, Wood for Trees is recognised as being the UK’s leading charity data analytics and database management business. We help charities and not-for-profit organisations make a difference, helping them generate and utilise their money more effectively by helping them get the most from their data. We’ve built a reputation for providing valuable insight, strategic advice and pragmatic action that can have a significant effect on the bottom line.

Our vision is to be the best data and analytics business in the charity sector. Being the best means we help our clients become data curious, ensure they get results and set the standard for sector trends and measurement.

About Inc & Co

Inc & Co is a Manchester-founded business group with retail, property, digital, food and beverage, and logistics brands. The group spans the UK with 250 staff and consists of incspaces (our UK-wide shared and flexible workspace), digital sports strategy agency Skylab and charity analytics firm Wood for Trees.

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