Data Science Intern in London

We are hiring a skilled and motivated Data Scientist on behalf of one of our clients for a fully remote opportunity.
The ideal candidate will have strong analytical and problem-solving skills, hands-on experience with data science tools, and the ability to transform complex datasets into actionable business insights.
Job Title
Data Scientist
Location
UK
Work Mode
100% Remote
Key Responsibilities
Gather, clean, transform, and analyse large datasets from diverse sources to generate meaningful insights.
Conduct exploratory data analysis (EDA) to uncover trends, patterns, correlations, and potential business opportunities.
Design, develop, train, and evaluate machine learning models for predictive analysis and forecasting.
Apply statistical methods, data modelling, and hypothesis testing to support informed business decisions.
Develop predictive algorithms and analytical solutions to address real-world business challenges.
Design interactive dashboards, reports, and data visualisations using Power BI, Tableau, Matplotlib, or Seaborn.
Extract, manipulate, and manage data using SQL while writing efficient and optimised queries.
Leverage Python libraries such as Pandas, NumPy, Scikit-learn, and SciPy for data analysis and machine learning.
Identify, investigate, and resolve data inconsistencies to maintain data accuracy, quality, and reliability.
Collaborate with data engineers, business analysts, software developers, and cross-functional teams.
Convert business requirements into actionable analytical solutions and present findings to relevant stakeholders.
Evaluate model performance, fine-tune algorithms, and continuously enhance predictive accuracy.
Automate data preparation, processing, and reporting tasks to streamline analytical workflows.
Perform feature engineering and feature selection to improve model efficiency and performance.
Maintain detailed documentation of analytical approaches, modelling techniques, workflows, and project deliverables.
Follow data privacy, security, governance, and compliance standards while handling sensitive information.
Required Skills & Qualifications
Strong programming skills in Python and SQL.
Good understanding of statistics, probability, and machine learning algorithms.
Hands-on experience with Pandas, NumPy, Scikit-learn, and data visualisation libraries.
Familiarity with Power BI or Tableau.
Excellent analytical, problem-solving, and communication skills.
A degree in Data Science, Computer Science, Statistics, Mathematics, or a related field is preferred.
Preferred Qualifications
Experience working with real-world datasets, predictive modelling, and advanced statistical analysis.
Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
Knowledge of deep learning frameworks such as TensorFlow, PyTorch, or Keras.
Experience with natural language processing (NLP), computer vision, or generative AI applications.
Understanding of big data technologies such as Apache Spark, Hadoop, or Databricks.
Experience with ETL pipelines, data integration, and data preprocessing workflows.
Familiarity with database systems such as PostgreSQL, MySQL, MongoDB, or Snowflake.
Knowledge of model deployment using Flask, FastAPI, Docker, or cloud-based services.
Understanding of MLOps practices, including model versioning, monitoring, and lifecycle management.
Experience using Git or other version control systems for collaborative development.
Familiarity with A/B testing, experimental design, and business performance metrics.
Ability to work with time-series data, forecasting techniques, and anomaly detection.
Experience developing scalable and production-ready machine learning solutions.
Understanding of responsible AI practices, model explainability, and bias detection.
Experience working in Agile environments and collaborating with cross-functional teams.
A portfolio of data science projects, research work, or contributions to open-source projects is an advantage.