Data Science Intern

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.