Junior Data Scientist

Information Tech Consultants; Greater London; On-site; GBP 42,000 - 64,000; Full time

Job summary

Information Tech Consultants in London is seeking a Junior Data Scientist with 2–5 years of experience to transform complex data into actionable insights. You will build predictive models, perform EDA, and deploy ML solutions in production using Python.

The role emphasizes hands-on development, collaboration with product and engineering teams, and clear communication of data-driven recommendations to stakeholders.

Qualifications

• Formal degree in a quantitative field.
• 2–5 years of data science experience.
• Hands-on ML deployment and productionization experience.

Responsibilities

• Design, develop, train, validate, and deploy ML models for business problems.
• Perform EDA, data cleaning, feature engineering on large datasets.
• Write production-quality Python for data processing and model creation.
• Collaborate with product managers, engineers, and stakeholders to present findings.

Skills

Python

ML frameworks

Pandas/NumPy/ SciPy

Statistics & Math

SQL & Databases

Big Data / Cloud

Data Visualization

Education

Bachelor's or Master's in a quantitative field

Tools

SQL

NoSQL

Spark

Hadoop

AWS

Azure

GCP

Tableau

Power BI

Job description

Junior Data Scientist

Location : London

Experience: 2–5 years

UK based candidates only - CITIZEN & DEPENDENTS

We are seeking an innovative and results-driven Data Scientist with a strong focus on Machine Learning and deep proficiency in Python. You will be instrumental in transforming complex data into actionable insights, building predictive models, and driving business strategy using cutting-edge analytical techniques. This role is for a hands-on individual who is excited to move models from the lab into production.

Key Responsibilities

• Model Development & Implementation: Design, develop, train, validate, and deploy advanced Machine Learning models (e.g., classification, regression, clustering, deep learning) to solve complex business problems.
• Data Wrangling & Analysis: Perform comprehensive Exploratory Data Analysis (EDA), data cleaning, feature engineering, and transformation on large, complex, and sometimes unstructured datasets.
• Coding & Automation: Write production-quality, highly efficient, and scalable code primarily in Python for data processing, analysis, and model creation.
• Experimentation & Optimization: Conduct A/B testing, hypothesis testing, and rigorous model validation, continually iterating and tuning algorithms to maximize performance, accuracy, and efficiency.
• Collaboration & Communication: Work closely with cross-functional teams (e.g., product managers, engineers, business stakeholders) to define project scope, interpret model results, and clearly present data-driven recommendations to both technical and non-technical audiences.
• Deployment & MLOps: Collaborate with ML/Data Engineers to deploy, monitor, and maintain ML models in a production environment, ensuring stability and performance over time.

Required Skills and Qualifications

Technical Expertise (The Core)

• Programming: Expert proficiency in Python and its core data science libraries: Pandas, NumPy, and SciPy.
• Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch.
• Statistics & Math: Strong foundation in statistical modeling, probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra for understanding model mechanics.
• Databases & Querying: Proficiency in SQL for extracting, manipulating, and preparing data from relational databases. Experience with NoSQL databases is a plus.
• Big Data/Cloud: Experience with big data tools (Spark, Hadoop) and cloud computing platforms (AWS, Azure, or GCP) for scalable ML workflows.
• Visualization: Ability to create clear, compelling data visualizations using tools like Matplotlib, Seaborn, Tableau, or Power BI to communicate insights.

Education & Experience

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
• [Number] years of professional experience as a Data Scientist or in a highly quantitative role.

Soft Skills (Your X-Factor)

• Curiosity: A strong passion for data and an inherent curiosity to explore, question, and challenge assumptions.
• Problem-Solving: Excellent analytical and structured thinking skills to tackle complex, ambiguous business problems.
• Storytelling: The ability to translate complex statistical and ML outputs into simple, business-relevant narratives and recommendations.