CO-HOSTED WEBINAR | FISCAL Technologies and Pagero | Tuesday 29 June | 15:00 BST | 10:00 EDT How to Protect Against the Increasing Risk of Fraud.

Junior Data Scientist


We’re a fast-growing technology company that’s continuing to expand its 1st class engineering team. In this pivotal role you’ll be doing more than just helping to define the vision for our products. You’ll contribute to the full software delivery cycle, from the beginnings of a new product idea, working through rapid prototypes, using customer validation as you define your backlogs, craft user stories and set the standard in your acceptance criteria.  Once we have our MVP, you’ll be working directly with customers verifying any new features are ready to take to market and how they can best be positioned.

What you’ll be doing…

We’re fast growing technology company that expanding its Data Science team. In this exciting time, we are now looking for a Junior Data Scientist with a degree or PhD in Statistics, Mathematics, Computer Science or another quantitative field.  The successful person will be working in the team to research and develop new tools as well as support various functional teams with insights gained from analysing client data.

The right candidate will have a passion for discovering insights hidden in large datasets and problem-solving

This role will interest people that are adept at using large datasets to identify opportunities for data pipeline optimisation, creation of tools that feed into product development and using data visualisation models to effectively inform clients of anomalous behaviour.


  • Automate processes for data pipeline optimisation
  • Process, cleanse and verify the integrity of data used for analysis
  • Engage in research tasks to develop new ML models for anomaly detection in time-series data
  • Develop processes and tools to monitor and analyse model performance
  • Work with stakeholders throughout the organisation to identify opportunities for leveraging client data to drive data-led business solutions

Qualifications/ Experience


  • 2-3 years’ experience of manipulating datasets and building statistical and/or Machine Learning (ML) models
  • Strong analytical and problem-solving skills
  • Proficient in using one or more statistical computer languages (Python, SQL, R etc.) to manipulate data and draw insights from large datasets
  • Knowledge of advanced statistical techniques and ML concepts (regression, properties of distributions, statistical tests and proper usage, clustering, decision tree learning, artificial neural networks etc.) and their real-world advantages/drawbacks
  • Experience using BI Tools such as Power BI or Tableau to set up dashboards with an emphasis on providing value to clients
  • Experience working with and creating data architectures/pipelines
  • Excellent written and verbal communication skills
  • A drive to learn and master new technologies and techniques


  • Experience in time-series analysis and anomaly detection
  • Knowledge of automated fraud detection techniques
  • Experience with deploying services in Azure

Need any more reasons to work with us?

It’s an exciting time to join FISCAL Technologies as we are expanding which will give you an opportunity to stand out and grow with us.

Established in 2003 and operating in the ‘Fintech’ space, FISCAL has approximately 50 employees, it is an environment where you will have an opportunity to make a big difference, we work hard but have a good time too!

We give back by supporting our chosen charity of the year and hold lots of fun events for employees to take part in. The company has been an award recipient multiple times for being a great place to work and we’re proud to hold a Queen’s award for innovation.

  • A flexible working policy,
  • Holiday buy & sell scheme
  • £500 per annum Wellbeing Allowance, including Perk box
  • Employer pension contribution and life assurance
  • An inclusive employee recognition scheme with monthly gift voucher prizes
  • Free on-site parking
  • Cycle to work scheme

    Apply Today

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