Junior Data Scientist

Intellect Group; Greater London; Hybrid; GBP 35,000 - 45,000; Full time

Job summary

A growing analytics team is seeking a Junior Data Scientist to support data-driven decision-making and applied statistical modeling. The ideal candidate will have a degree in a related field and strong skills in Python and data analysis. Responsibilities include analyzing datasets, building predictive models, and collaborating with teams to apply insights. This role offers mentorship and growth opportunities in a supportive environment.

Qualifications

• Strong proficiency in data analysis libraries like Pandas and NumPy.
• Solid understanding of basic machine learning techniques.
• Ability to communicate insights clearly, both in writing and verbally.

Responsibilities

• Analyse and interpret large datasets to uncover trends and actionable insights.
• Build and evaluate statistical models and machine learning algorithms.
• Create clear visualisations and dashboards to communicate findings.

Skills

Data analysis

Python

SQL

Statistics

Communication

Education

Bachelor’s or Master’s degree in Data Science or related field

Tools

Pandas

NumPy

scikit-learn

Matplotlib

Seaborn

Job description

Junior Data Scientist

Location: London (3 days per week in office, rest remote)

Salary: £35,000 – £45,000 DOE

We are looking for a Junior Data Scientist to join a growing analytics team working on data-driven decision-making and applied statistical modelling. This role is ideal for someone with a strong academic or early-career foundation in data analysis who is keen to apply their skills to real-world business problems, working with structured data, modern analytics tools, and stakeholders across the organisation.

You’ll play a key role in analysing datasets, building predictive and descriptive models, and supporting data-led initiatives, while receiving mentorship and support to grow into a more specialised data science role.

Key Responsibilities:

• Analyse and interpret large datasets to uncover trends, patterns, and actionable insights.
• Clean, preprocess, and transform data from multiple sources (CSV, Excel, SQL databases, APIs).
• Build and evaluate statistical models and machine learning algorithms for forecasting, classification, and segmentation.
• Create clear visualisations and dashboards to communicate findings to technical and non-technical audiences.
• Support the development of end-to-end data pipelines, ensuring data quality and reproducibility.
• Collaborate with product, engineering, and business teams to translate analytical results into practical outcomes.
• Document methodologies, assumptions, and results to ensure knowledge sharing and transparency.

Required Skills & Experience:

• A Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field.
• Strong proficiency in Python and common data analysis libraries (e.g., Pandas, NumPy, scikit-learn, Matplotlib/Seaborn).
• Solid understanding of statistics, exploratory data analysis, and basic machine learning techniques.
• Experience working with SQL and relational databases.
• Ability to communicate insights clearly, both in writing and verbally.
• Familiarity with version control and collaborative workflows (e.g., Git).

Desirable Skills:

• Experience with data visualisation or BI tools (e.g., Tableau, Power BI, Looker).
• Exposure to cloud-based data platforms or analytics tools (AWS, GCP, Azure).
• Basic knowledge of experiment design and A/B testing.
• Interest in applying data science to domains such as marketing, finance, operations, or customer analytics.

This is a fantastic opportunity for a motivated early-career data scientist who wants to build a strong foundation in applied data science, contribute to meaningful projects, and grow within a collaborative, forward-thinking environment.