• Data Analyst (Newcastle, Edinburgh, Dundee)

    Location UK-Newcastle upon Tyne
    Job ID
    # Positions
    Category (Candidate Search)
    Position Type
    Business Group
    SolarWinds MSP
  • Overview

    SolarWinds MSP is the leading global provider of complete IT management and Automation solutions for Managed Service Providers (MSPs). Our award-winning product suite includes the industry’s #1 RMM Service Automation Platform and has a proven track record of helping MSPs standardise and automate the setup and delivery of IT services in order to achieve true scalability.  


    Solarwinds MSP is the leader of empowering MSPs with data. We are constantly pushing the envelope with regard to how data is ingested, stored and used in product. The Data Science team is chartered to seed and influence product improvements based on value in data, and as such, is a key stakeholder in all aspects of the data lifecycle.  


    As a Data Analyst in this team you will have a healthy appetite for continuous learning in areas such as machine learning, data visualisation and the latest Data Science trends. You will be working closely with other Data Analysts and Scientists to improve the MSP set of products with data-driven features that measurably improve the effectiveness and efficiency of the company, our customers and our customers’ customers. 



    • Collaborate on strands of Data Science work and/or multiple projects that discover opportunities for new data-driven features, and influence product and technology strategies for the MSP product. 
    • Create rapid prototypes of data analytics features and work closely with engineering to convert these into high-quality reusable services to be used in the product.
    • Communicate research results effectively in written and spoken forms to various audiences including product management, engineering, executives, and customers.
    • Keep abreast of emerging technologies and best practices and share this knowledge within the team, within the company and externally.
    • Promote self-service data analysis and understanding by sharing knowledge using internal presentations and publications.  



    • Working experience in relevant technical fields (or equivalent, e.g. significant personal/part-time projects).
    • Interest and understanding of some of the typical methodologies in Data Science (e.g. statistics, machine learning, deep learning, …).
    • Interest and understanding of some of the typical tooling in Data Science (e.g. core: R/Python; data querying: SQL, Spark, Hive; data presentation: ggplot/seaborn, knitr/jupyter, Shiny/Dash; deep learning frameworks: e.g. Tensorflow).
    • A research mindset.
    • Passion for exploring emerging methodologies and technology stacks. 
    • A solid “can do” attitude while also being aware that it’s never too soon to ask for help on any topic.
    • Independent, self-organizing, and able to prioritize multiple complex assignments.
    • Understanding of best practices in data handling, security and privacy. 

    Extra Credit: 

    • Relevant experience in related fields, e.g. software engineering, statistics, computer science, scientific research, … .
    • Practical experience in delivering data-driven applications/APIs at scale.
    • Practical experience dealing with big data challenges in any of the three Vs: volume, velocity, variety.
    • Experience with any of Linux, Git, Docker, Kubernetes, AWS or Kafka.
    • Experience of presentations or publications on technical topic


    What is in it for you: 

    • We offer great compensation packages including company bonus, pension and health insurance. On top of this you will have the opportunity to solve challenging problems with skilled colleagues but also a team committed to work/life balance with fewer meetings. 



    Apply/Socialize Options

    Sorry the Share function is not working properly at this moment. Please refresh the page and try again later.
    Share on your newsfeed

    Connect With Us!

    Not ready to apply? Connect with us for general consideration.