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General information

Posting ID
PIP7831
Type of employment
Contract
Organisation
Office for National Statistics
Contract duration
6 Months
Location
Newport
Workplace Type
Hybrid

Description & Requirements

On behalf of ONS, we are looking for an Associate Data Scientist (INSIDE IR35) for a 6 month contract based Hybrid in Newport or Titchfield.


About the Role

ONS is building a brand new early career Data Scientist talent pipeline to grow the next generation of data professionals supporting the UK’s most important statistics.

This is a fantastic opportunity for people with foundational data science skills who are looking to develop quickly, gain hands on experience and contribute to projects that impact millions of people across the UK.

You’ll join as an Associate Data Scientist (HEO), working within multidisciplinary teams alongside experienced Data Scientists, Data Engineers and Software Engineers. You’ll contribute to the development of analytical models, data pipelines and statistical products that underpin core UK government data.


As an Associate Data Scientist (HEO) your main responsibilities will include:

  • Preparing, cleaning and transforming datasets for analysis.
  • Running exploratory data analysis and producing visual insights.
  • Building and testing simple machine‑learning models under guidance.
  • Contributing to data science projects used in national statistics, forecasting and research.
  • Working with Data Engineers and senior DS colleagues to deliver quality‑assured outputs.
  • Learning new tools, techniques and technologies as part of structured development pathways.
  • This role suits someone with solid academic grounding and early hands‑on experience who wants to grow fast.


Essential:

  • Experience using Python or R to write scripts and build basic models.
  • Understanding of statistics and model evaluation metrics.
  • Ability to clean, prepare and manipulate data.
  • Ability to explain findings to both technical and non-technical audiences.
  • Curious, analytical mindset with a desire to learn and grow.


Desirable:

  • A degree in Data Science, Maths, Statistics, Computer Science or related field or equivalent practical experience.
  • Exposure to cloud environments (e.g., AWS or Azure).
  • Familiarity with data visualisation tools (PowerBI, Plotly or similar).
  • Some experience with machine learning libraries (such as Scikit‑learn).
  • Basic understanding of Agile or collaborative delivery methods.


Please be aware that this role can only be worked within the UK and not Overseas.


Disability Confident 

As a member of the Disability Confident Scheme, ONS guarantees to interview all candidates who have a disability and who meet all the essential criteria for the vacancy. In cases where we have a high volume of candidates who have a disability who meet all the essential criteria, we will interview the best candidates from within that group.

This scheme encourages candidates with a disability and/or neurodivergence to apply. In exceptional circumstances, we may also need to apply the desirable criteria in our shortlisting process which may include holding active security clearance.


Armed Forces Covenant 

ONS guarantees to interview veterans or spouses / partners of military personnel who meet all the essential criteria for the vacancy. In cases where we have a high volume of ex-military candidates / military spouses or partners, who meet all of the essential criteria, we will interview the best candidates from within that group. In exceptional circumstances, we may also need to apply the desirable criteria in our shortlisting process which may include holding active security clearance.

In applying for this role, you acknowledge the following "this role falls in scope of the Off Payroll Working in the Public Sector legislation. Any rates of payment quoted will reflect the gross rate per day for the assignment and will be subject to appropriate taxes and statutory costs. As such the payment to the intermediary and your income resulting from this contract will be different".